WO2014053679A1 - Method and system for determining the freshness of fish, based on the processing of ocular images, and computer program implementing the method - Google Patents

Method and system for determining the freshness of fish, based on the processing of ocular images, and computer program implementing the method Download PDF

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Publication number
WO2014053679A1
WO2014053679A1 PCT/ES2013/000220 ES2013000220W WO2014053679A1 WO 2014053679 A1 WO2014053679 A1 WO 2014053679A1 ES 2013000220 W ES2013000220 W ES 2013000220W WO 2014053679 A1 WO2014053679 A1 WO 2014053679A1
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Prior art keywords
fish
image
freshness
computing device
eye
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PCT/ES2013/000220
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Spanish (es)
French (fr)
Inventor
Miguel De La Guardia Cirugeda
Majid DOWLATI
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Universitat De Valencia
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Publication of WO2014053679A1 publication Critical patent/WO2014053679A1/en

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    • A—HUMAN NECESSITIES
    • A22—BUTCHERING; MEAT TREATMENT; PROCESSING POULTRY OR FISH
    • A22C—PROCESSING MEAT, POULTRY, OR FISH
    • A22C25/00—Processing fish ; Curing of fish; Stunning of fish by electric current; Investigating fish by optical means
    • A22C25/04—Sorting fish; Separating ice from fish packed in ice
    • A—HUMAN NECESSITIES
    • A22—BUTCHERING; MEAT TREATMENT; PROCESSING POULTRY OR FISH
    • A22C—PROCESSING MEAT, POULTRY, OR FISH
    • A22C17/00—Other devices for processing meat or bones
    • A22C17/0073—Other devices for processing meat or bones using visual recognition, X-rays, ultrasounds, or other contactless means to determine quality or size of portioned meat
    • A22C17/008—Other devices for processing meat or bones using visual recognition, X-rays, ultrasounds, or other contactless means to determine quality or size of portioned meat for measuring quality, e.g. to determine further processing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/02—Food
    • G01N33/12—Meat; fish

Definitions

  • the present invention concerns in general, a method, a system and a computer program, for determining the freshness of the fish based on the processing of ocular images, and more particularly a procedure comprising determining the freshness of the fish by interpolating values of parameters of the CIELab space of an image acquired in one or more calibration curves.
  • Freshness is the most important attribute of fish quality. Freshness is a complex concept but can be estimated as a combination of several sensory properties such as appearance, smell, taste and texture.
  • the sensory evaluation of the freshness of the fish uses a scheme well defined by the Index Method of
  • QIM Quality of Matter
  • Bogdanovic T, et al, 2012 applied by a trained panel of people; This method allows a safe quantitative evaluation of freshness.
  • Such panels are expensive, their instruction is critical and the panel is not always accessible. Therefore, to satisfy the need for quality measures in industry, commerce or in the consumer, instrumental methods are necessary to date.
  • Photographic images have also been used to evaluate biometric parameters of the samples (length, weight) (Gümüs et al. 2011; Olafsdottir et al. 2004; Hosseini et al 2008) or as complementary support for sensory studies.
  • Application EP2189789 A1 describes a procedure for checking the freshness of a fish that comprises detecting the eye by means of a contour detection algorithm and identifying the center of the pupil as the accumulated of multiple centroids.
  • the device that performs this operation consists of a tunnel where the fish tray passes in which two lighting sources (fluorescent tubes) are located on both sides of the tray that provide diffused lighting, necessary to avoid shadows that would alter the measurement.
  • An image capture device for example a CCD camera, is placed vertically on the tray to capture images of the eye.
  • the shape of the eye varies over time since its capture and that variation in shape, correlated with other freshness assessment procedures, allows the procedure to be calibrated.
  • Muhamad et al., 2009 shows the determination of the freshness of the fish by acquiring, among others, an image of the fish's eye and the determination and processing of color parameters of the acquired image. Specifically, it evaluates the usefulness of a procedure to classify a fish according to its level of freshness that is based on processing images of the eye and gills using fuzzy logic techniques. Samples were taken over five days and the evolution of gill and eye color parameters, in particular RGB color index values, was studied according to two models or methods to determine which of them best suited to The experimental results.
  • Muhamad et al., 2009 constitutes a teaching that induces the person skilled in the art to move it away from the search for a solution aimed at making such a determination by analyzing color parameters of fish images, which include ocular images, and in particular of solutions based on the analysis of only ocular images.
  • Mateo et al., 2006 describes a system for the automated inspection of the color of tuna meat to determine its quality.
  • the procedure is based on automating the acquisition of images of the pieces of meat by means of a device consisting of a chamber covered by a bell structure in PVD in which the sample that is illuminated by means of LED or fluorescent tube lights is located .
  • a CCD camera is located perpendicular on the area where the sample is located to collect the images.
  • These are translated in color terms according to CIELab color space.
  • the parameters L, a and b are correlated with the scores that a human classifying agent would grant and calibration curves are established.
  • the present invention provides an alternative to the state of the art that aims to improve the results obtained by the known proposals for determining the freshness of the fish based on the analysis of color parameters of ocular images thereof, as described in the article " Fishfreshness classification based on image processing and fuzzylogic "whose poor results are clearly improvable.
  • the present invention concerns a method for determining the freshness of the fish based on the processing of ocular images, comprising:
  • step b) comprises:
  • step b2) the determination in the image of step b1) of at least one of the parameters L * , a * and / or * of the CIELab space and its corresponding value;
  • step b3) the interpolation of the value obtained in step b2) in at least one calibration curve generated from values obtained with specimens of the same type, after performing a plurality of said stages a), b1) and b2) for images , acquired under these determined conditions, from the eyes of different samples of reference fish of the species to be analyzed, for different freshness values.
  • the method further comprises a step c) of determining the freshness of the sample of the target fish from the value interpolated in step b3).
  • freshness is understood as the time elapsed since the capture of the fish during which the fish has been kept refrigerated at 0 ° C or below 0 ° C without reaching its freezing point (which in general is about - 1, 5 ° C).
  • the freshness can be expressed in days, months, hours, or any other temporary measure. Preferably, the freshness is expressed in days.
  • the process comprises, in step c), providing the value of the freshness determined in terms of days when the fish has been kept at 0 degrees or below 0 ° C without reaching its freezing point .
  • the calibration curve is a curve that relates at least one of the parameters L *, to * and / or * with days when the fish has been kept at 0 degrees or below 0 ° C without reaching its freezing point.
  • the method comprises, for some embodiments, determining in step b2) several of the indicated parameters, and using, in step b3), several calibration curves referring to said parameters.
  • the method comprises using in step b3) calibration curves referring to obvious combinations of the mentioned parameters, such as L * + a *, a * - b *, etc., and interpolating the values of the parameters determined in step b2) after combining them in the same way.
  • steps b1), b2), b3) and c) are performed automatically.
  • step b) is performed on the part of the acquired image corresponding to the iris of the fish's eye.
  • the method comprises generating and storing at least said calibration curve.
  • the storage in memory of the calibration curve refers to storage in any kind of memory or equivalent device known, either in a local system or in a remote one, or a combination thereof.
  • the process of the first aspect of the invention allows the rapid measurement of the freshness of the fish without using a trained panel of tasters or instrumental methods.
  • the procedure allows the determination of the freshness of the fish based exclusively on the processing of different parameters of digital images (photos) that are compared with a data library.
  • the appearance of the eyes has a good relationship with the freshness of the fish. Some of the factors that are considered in the appearance of the eyes are clarity, darkness, color and color concentration.
  • images of the eyes of the specimens are used and by means of the digital image processing the freshness of the fish is determined using simple parameters and / or combinations thereof.
  • the acquired image is a digital image obtained by a digital camera, under certain conditions that include using a distance between the fish's eye and the camera lens in a range between 10-30 cm and using a lighting source between 2500 and 6500 Kelvin degrees of color temperature.
  • the values by which said calibration curve has been generated have been obtained for images of the eyes of the different samples of reference fish kept at a temperature of 0 degrees Celsius or slightly below this .
  • the processing of the raw data of the image of step b1) includes a preprocessing or initial processing of the raw data of the image acquired in step a) for the correction of deformations geometric, noise elimination, gray level correction and cloud correction.
  • the method comprises, according to an embodiment example:
  • step b1) - performing said segmentation of step b1) on the pre-processed image in a plurality of areas of interest to set the color parameters with respect to the iris of the eye of the fish sample;
  • the method comprises, according to an embodiment example, comparing, manually or automatically, the freshness value determined in step c) with the actual freshness value of the sample of the target fish to verify whether the chain has been maintained of cold.
  • the process of the first aspect of the invention comprises:
  • V send, from the remote computing device to the portable computing device, the freshness value determined in step c).
  • step ii) comprises sending the acquired image and step iii) also comprises carrying out, by the remote computing device, steps b1) and b2).
  • the method comprises performing steps b1) and b2) by the portable computing device, and stage ii) comprises sending said information associated with the acquired image, said information being the value or values determined in the stage b2).
  • the method comprises, prior to said stage iii), sending, the user, from the portable computing device to the remote computing device, together with the sending of the image, or prior or later, a signal indicating the species to which the sample of target fish, in order to perform step b3) on calibration curves related to that species.
  • the method proposed by the first aspect of the invention comprises performing the steps described for a plurality of objective fish simultaneously, including the image acquired image data relating to the eyes of said plurality of target fish. .
  • the method of the first aspect of the invention includes a calibration such that it allows the rapid determination of the freshness of the fish through exclusively the treatment of digital images obtained by non-specialized personnel.
  • a second aspect of the invention concerns a system for determining the freshness of the fish based on the processing of ocular images, configured to implement the procedure of the first aspect, and comprising:
  • step b an electronic system, in connection with said image acquisition means to receive the acquired images, and which is configured to implement step b).
  • the electronic system is configured to implement steps b1), b2), b3) and c) of the procedure, comprising or having access to at least one memory where the calibration curve or curves are registered to perform step b3).
  • the electronic system can be located in any kind of remote system, such as commonly known as "cloud”, and access it through any type of network of communications.
  • the image acquisition means comprise:
  • the auxiliary separating device comprises lighting means arranged and configured to illuminate said fish eye through the longitudinal hole of said body.
  • the lighting means comprise a light source introduced, at least partially, into a transverse through hole made in a wall of the body, to illuminate the interior of the longitudinal hole.
  • said through transverse hole has a diameter of between 2 to 5 cm and is located at a height of between 2.5 to 7.5 cm from the base of the body to be arranged on the fish.
  • the system is adapted to implement the aforementioned exemplary embodiment of the procedure of the first aspect which refers to the realization of steps i) to v), and which comprises:
  • a portable computing device such as a smartphone, a PDA, etc.
  • communications capability preferably wireless, that includes said digital camera and a local part of said electronic system to implement stages i) and ii ) of the first aspect procedure
  • a remote computing device with communications capability preferably wireless, that includes a remote part of said electronic system to implement steps iii) and iv) of the procedure.
  • the system proposed by the second aspect of the invention also comprises the auxiliary separator device described above, to be used together with the portable computing device to implement step i).
  • the portable computing device has a screen to show the freshness value received in stage iv).
  • a third aspect of the invention concerns a computer program adapted to execute the procedure of the first aspect, including performing steps b1), b2), b3) and c).
  • the computer program comprises a first executable software application by the portable computing device and a second executable software application by the remote server, being carried out, between both applications, the previously described stage ii ) to iv).
  • the first software application allows the user to make the selection of the species to which the target fish sample belongs, which will cause the computing device to send the corresponding signal signal to the remote computing device.
  • Figs. 1, 2 and 3 show a calibration curve based on, respectively, the parameters L *, a * and b *, generated and used in accordance with the procedure proposed by the first aspect of the invention, for some examples of embodiment;
  • Fig. 4 shows the temporal evolution of the parameter ⁇ calculated for the values shown in the curves of Figs. 1 to 3 regarding initial values.
  • Fig. 5 is a graph that shows the changes that the L * parameter undergoes in terms of fish conservation, for different thermal storage conditions, for three sample fish, two of which are deteriorated fish because it has been broken the cold chain for them;
  • Figs. 6 and 7 are graphical paths analogous to that of Fig. 5 but in relation to, respectively, the variation of parameter a * and parameter b * ; Y
  • Fig. 8 is a schematic perspective view of the image acquisition means of the system proposed by the second aspect of the invention, for an exemplary embodiment.
  • the method of the first aspect of the invention comprises, for an exemplary embodiment, a first image acquisition step E1.
  • a digital image of the fish's eyes is taken in very specific conditions: distance between the fish eye and the camera lens in an interval between 10 and 30 cm, with a controlled illumination of the order of 2500-6500 degrees Kelvin.
  • These conditions can be achieved by a cylindrical or conical device open at its ends, made of a non-transparent and white material, between 10-30 cm high, with a hole of 2-5 cm in diameter, located at a height between 2.5-7.5 cm from the base and a fluorescent or LED light source, as illustrated in Fig. 8, which is will describe later with reference to the system proposed by the second aspect of the invention.
  • the acquisition of the image is reflected in the transfer of the electronic signal of the photographic device in numerical form and allows, after a preprocessing, or step E2, to establish parameters that are those that will be used to evaluate the freshness of the fish.
  • the preprocessing of the E2 image refers to the initial processing of the raw image data for the correction of geometric deformations, the elimination of noise, the gray level correction and the clouding correction.
  • the segmentation of the image, or stage E3 allows it to be divided into regions that have a great correlation with the objects or areas of interest. In the present case, it is about setting the iris parameters of the sample eye.
  • stage E4 of recognition of the fish eye is carried out centering the image on it, and after this the parameters are determined in the iris: L *, a * and / ob *, in a stage E5 of extraction of parameters, which allow the images to be correlated with the freshness of the fish in the CIE L * a * b * (CIELAB) space, which is the most complete color model conventionally used to describe all colors visible to the human eye. It was developed for this specific purpose by the International Lighting Commission.
  • stage E6 is the interpolation of the color parameters in the previously established calibration curve with reference samples, of the same species to be evaluated, to determine the freshness (defined as days elapsed since the death of the fish, having kept it at zero degrees Celsius). The determination can be made using a single color parameter or combinations thereof.
  • the calibration has been previously constructed from a library of images of sample fish, which is different for each species, and that were taken under certain lighting conditions that must be kept fixed in all new measures to obtain a correct determination .
  • the calibration curves to be used according to the procedure proposed by the first aspect of the invention are shown in Figs. 1 to 3 for, respectively, the parameters L *, a * and b *.
  • a curve relative to the parameter ⁇ is shown in Fig. 4.
  • This is a parameter relative to the total color difference, which takes into account the individual differences between the value of each parameter L * , a * and b * as a function of time and the value of each taken at zero time; that is, the value of each parameter obtained for each elapsed day, and the starting value for a zero time (freshly killed fish), and is used to verify the independence of the calibration curves obtained for the parameters L *, a * and b *.
  • ⁇ * ((L * ⁇ - L * 0 ) 2 + (a * , - a * 0 ) 2 + (b * ⁇ - b * 0 ) 2 ) 1 ' 2
  • the subscripts i and 0 refer respectively to the values taken for each day elapsed and those taken at zero time.
  • stage E7 a classification of the fish is made based on the freshness determined as a result of stage E6.
  • the eye recognition, as well as all the stages of image processing, parameter extraction and extrapolation in the calibration are carried out using software developed in MATLAB environment.
  • the procedure proposed by the first aspect of the invention also serves, for some examples of embodiment, as a method of controlling the thermal traceability of fish, that is, to detect changes in maintenance / fish storage.
  • the study of the evolution of the image parameters of the eyes of gilthead specimens that had been preserved for a time at room temperature (25 ° C) has been carried out in order to verify the effects of breaking the cold chain (0 ° C) on the freshness of the fish.
  • Figures 5 to 7 show for three specimens under study (indicated as P1, P2 and P3) that the breaking of the cold chain affects the parameters of the images, denouncing a state of freshness equivalent to an increase in storage time . It is noteworthy that this effect is evidenced by the parameters L *, a * and / ob *; being able to obtain improvements in the detection of the interruption of the cold chain using products or quotients of the previous parameters. Specifically, the curves illustrated in Figs.
  • 5 to 7 show the changes that the L *, a * and b * parameters undergo fish conservation, for different thermal storage conditions, over five days (indicated as d1 to d5) for three sample fish P1, P2 and P3, and have been created from reference data obtained in turn from the values obtained after performing a plurality of stages a), b1), b2, b3) and c) on images acquired from The eyes of the sample fish P1, P2, P3, for different degrees of conservation temperature over time.
  • sample fish P3 has been kept at zero degrees in the periods dO to d1 (that is, during the first day of storage since fishing), d1 to d1 + 8h and d3 to d5, and 25 degrees in periods d1 + 8h to d2 and d2 to d3, and fish P2 has been maintained at zero degrees for all periods indicated except for the period from d1 + 8h to d2.
  • FIG. 8 An implementation of the system proposed by the second aspect of the invention is illustrated in Fig. 8, for an exemplary embodiment for which it comprises:
  • a portable computing device M with communications capability which includes a digital camera C with a lens L and a local part of the electronic system (not illustrated) to implement steps i) and ii);
  • auxiliary separator device D to be disposed between the lens L of the digital camera C and the fish eye (not illustrated) whose image is to be acquired, which is formed by a body B of non-transparent material between 10-30 cm of height with a longitudinal through hole 01, of geometric axis E, to lightly communicate both the lens L of the chamber C and the eye of the fish, when disposed between them;
  • the transverse through hole 02 preferably has a diameter between 2 to 5 cm and is located at a height between 2.5 to 7.5 cm from the base of the body B to be arranged on the fish, that is to say from the lower base according to the position illustrated in Fig. 8.
  • the separating auxiliary device D has been described and claimed as part of the means of acquiring the system proposed by the second aspect of the invention, it could be object of independent protection for the application described herein or other applications that require the conditions of image acquisition, especially in terms of distance between the lens and the object to be photographed, required by the application referring to the procedure proposed by the first aspect of the present invention.

Abstract

The invention relates to a method comprising: a) the acquisition, under pre-defined conditions, of an image of the eye of a target fish; b1) the processing of the raw data of the acquired image and the segmentation of the image in order to set colour parameters; b2) the determination of parameters L*, a* and/or b* and the corresponding value thereof; b3) the interpolation of the value obtained in step b2) in a calibration curve generated from values obtained following a plurality of steps a), b1), and b2), for certain images, acquired under said pre-defined conditions, of the eyes of different reference fish samples; and c) the determination of the freshness of the target fish sample from the value interpolated in step b3). The system is suitable for implementing the method of the invention. The computer program implements the method of the invention.

Description

Procedimiento y sistema para determinar la frescura del pescado basado en el procesamiento de imágenes oculares, y programa de ordenador que implementa el procedimiento Objeto de la invención  Procedure and system to determine the freshness of the fish based on the processing of ocular images, and computer program that implements the procedure Object of the invention
La presente invención concierne en general, a un procedimiento, un sistema y un programa de ordenador, para determinar la frescura del pescado basado en el procesamiento de imágenes oculares, y más en particular a un procedimiento que comprende determinar la frescura del pescado interpolando unos valores de parámetros del espacio CIELab de una imagen adquirida en una o más curvas de calibrado.  The present invention concerns in general, a method, a system and a computer program, for determining the freshness of the fish based on the processing of ocular images, and more particularly a procedure comprising determining the freshness of the fish by interpolating values of parameters of the CIELab space of an image acquired in one or more calibration curves.
Estado de la técnica anterior Prior art
La frescura es el atributo más importante de la calidad de pescado. La frescura es un concepto complejo pero puede ser estimado como una combinación de varias propiedades sensoriales como apariencia, olor, sabor y textura. La evaluación sensorial de la frescura del pescado utiliza un esquema bien definido por el Método de índice de Freshness is the most important attribute of fish quality. Freshness is a complex concept but can be estimated as a combination of several sensory properties such as appearance, smell, taste and texture. The sensory evaluation of the freshness of the fish uses a scheme well defined by the Index Method of
Calidad (QIM) (Bogdanovic T, et al, 2012) aplicado por un panel entrenado de personas; este método permite dar una evaluación cuantitativa segura de la frescura. Sin embargo, tales paneles son caros, la instrucción de los mismos es crítica y el panel no es siempre accesible. Por consiguiente, para satisfacer la necesidad de medidas de calidad en la industria, el comercio o en el consumidor, los métodos instrumentales son necesarios hasta la fecha. Quality (QIM) (Bogdanovic T, et al, 2012) applied by a trained panel of people; This method allows a safe quantitative evaluation of freshness. However, such panels are expensive, their instruction is critical and the panel is not always accessible. Therefore, to satisfy the need for quality measures in industry, commerce or in the consumer, instrumental methods are necessary to date.
En el estado de la técnica se describen procedimientos para la determinación de la frescura del pescado basados en análisis químicos, bioquímicos o microbiológicos (a través de medidas físicas) o mediante análisis sensorial completo (ver las referencias al final del texto). También se han empleado imágenes fotográficas para evaluar parámetros biométricos de las muestras (longitud, peso) (Gümüs et al. 2011 ; Olafsdottir et al. 2004; Hosseini et al 2008) o como apoyo complementario a estudios sensoriales.  Procedures for determining the freshness of the fish based on chemical, biochemical or microbiological analysis (through physical measurements) or by complete sensory analysis (see references at the end of the text) are described in the state of the art. Photographic images have also been used to evaluate biometric parameters of the samples (length, weight) (Gümüs et al. 2011; Olafsdottir et al. 2004; Hosseini et al 2008) or as complementary support for sensory studies.
Existe una aplicación para iPhone (Howfreshisyourfish?) desarrollada por Nofima basada en un protocolo QIM, que incluye el empleo de fotos además de otras pruebas sensoriales, incluyendo el olor, textura y apariencia de los ojos, piel y branquias.  There is an iPhone application (Howfreshisyourfish?) Developed by Nofima based on a QIM protocol, which includes the use of photos in addition to other sensory tests, including the smell, texture and appearance of the eyes, skin and gills.
La solicitud EP2189789 A1 describe un procedimiento para comprobar la frescura de un pescado que comprende detectar el ojo mediante un algoritmo de detección de contornos e identificar el centro de la pupila como el acumulado de múltiples centroides. El dispositivo que lleva a cabo esta operación consiste en un túnel por donde pasa la bandeja de pescado en el que se sitúan dos fuentes de iluminación (unos tubos fluorescentes) a ambos lados de la bandeja que proporcionan una iluminación difusa, necesaria para evitar sombras que alterarían la medición. Un dispositivo de captura de imágenes, por ejemplo una cámara CCD, se sitúa verticalmente sobre la bandeja para capturar imágenes del ojo. La forma del ojo varía con el transcurso del tiempo desde su captura y esa variación de forma, correlacionada con otros procedimientos de evaluación de frescura, permite calibrar el procedimiento. Application EP2189789 A1 describes a procedure for checking the freshness of a fish that comprises detecting the eye by means of a contour detection algorithm and identifying the center of the pupil as the accumulated of multiple centroids. The device that performs this operation consists of a tunnel where the fish tray passes in which two lighting sources (fluorescent tubes) are located on both sides of the tray that provide diffused lighting, necessary to avoid shadows that would alter the measurement. An image capture device, for example a CCD camera, is placed vertically on the tray to capture images of the eye. The shape of the eye varies over time since its capture and that variation in shape, correlated with other freshness assessment procedures, allows the procedure to be calibrated.
Muhamad et al., 2009 muestra la determinación de la frescura del pescado mediante la adquisición de, entre otras, una imagen del ojo del pescado y la determinación y el procesamiento de unos parámetros de color de la imagen adquirida. En concreto, evalúa la utilidad de un procedimiento para clasificar un pescado de acuerdo a su nivel de frescura que se basa en procesar imágenes del ojo y de las agallas utilizando técnicas de lógica difusa. Se tomaron muestras a lo largo de cinco días y se estudió la evolución de los parámetros de color de agallas y ojos, en particular de valores de índices de color RGB, de acuerdo a dos modelos o métodos para determinar cuál de ellos se ajustaba mejor a los resultados experimentales. Con ambos métodos los resultados obtenidos fueron muy deficientes, ya que incluso con el método que ofreció mejores resultados se obtuvo un error de un 44% frente al resultado esperado, concluyendo los propios inventores que la utilización de estos métodos basados en la lógica difusa implica demasiados errores en la determinación de la frescura del pescado.  Muhamad et al., 2009 shows the determination of the freshness of the fish by acquiring, among others, an image of the fish's eye and the determination and processing of color parameters of the acquired image. Specifically, it evaluates the usefulness of a procedure to classify a fish according to its level of freshness that is based on processing images of the eye and gills using fuzzy logic techniques. Samples were taken over five days and the evolution of gill and eye color parameters, in particular RGB color index values, was studied according to two models or methods to determine which of them best suited to The experimental results. With both methods the results obtained were very poor, since even with the method that offered better results, an error of 44% was obtained compared to the expected result, concluding the inventors themselves that the use of these methods based on fuzzy logic implies too many errors in determining the freshness of the fish.
Asimismo, en la determinación propuesta por Muhamad et al., 2009 se analizan los parámetros RGB de ambos, los ojos y las agallas del pescado, no proponiéndose realizar tal determinación únicamente sobre las imágenes oculares.  Likewise, in the determination proposed by Muhamad et al., 2009, the RGB parameters of both the eyes and the gills of the fish are analyzed, with no such determination being made solely on the ocular images.
Por lo tanto Muhamad et al., 2009 constituye una enseñanza que induce al experto en la materia a alejarlo de la búsqueda de una solución encaminada a realizar tal determinación analizando parámetros de color de imágenes del pescado, que incluyan imágenes oculares, y en particular de soluciones basadas en el análisis de únicamente imágenes oculares.  Therefore Muhamad et al., 2009 constitutes a teaching that induces the person skilled in the art to move it away from the search for a solution aimed at making such a determination by analyzing color parameters of fish images, which include ocular images, and in particular of solutions based on the analysis of only ocular images.
Finalmente Mateo et al., 2006 describe un sistema para la inspección automatizada del color de la carne de atunes para determinar su calidad. El procedimiento se basa en automatizar la adquisición de imágenes de las piezas de carne mediante un dispositivo que consiste en una cámara cubierta de una estructura de campana en PVD en la que se emplaza la muestra que se ilumina mediante unas luces de LED o de tubo fluorescente. En perpendicular sobre la zona donde se ubica la muestra se sitúa una cámara CCD para recoger las imágenes. Estas son traducidas en términos de color de acuerdo al espacio de color CIELab. Los parámetros L, a y b son correlacionados con las puntuaciones que otorgaría un agente clasificador humano y se establecen unas curvas de calibración. Finally Mateo et al., 2006 describes a system for the automated inspection of the color of tuna meat to determine its quality. The procedure is based on automating the acquisition of images of the pieces of meat by means of a device consisting of a chamber covered by a bell structure in PVD in which the sample that is illuminated by means of LED or fluorescent tube lights is located . A CCD camera is located perpendicular on the area where the sample is located to collect the images. These are translated in color terms according to CIELab color space. The parameters L, a and b are correlated with the scores that a human classifying agent would grant and calibration curves are established.
No se conoce ninguna propuesta para determinar la frescura del pescado basada en la determinación de los parámetros del espacio de color CIELab sobre imágenes del ojo del pescado, ni la utilización con curvas de calibración que no requieran de la intervención de un agente clasificador humano.  There is no known proposal to determine the freshness of the fish based on the determination of the CIELab color space parameters on fish eye images, nor the use with calibration curves that do not require the intervention of a human classifying agent.
A la vista de los documentos del estado de la técnica más relevantes mencionados anteriormente, tanto individualmente como en combinación, la presente invención no resulta evidente. Muhamad et al. 2009, muestra la determinación de la frescura del pescado a partir de imágenes de ambos ojos de pescado basado en la determinación de los parámetros RGB, y no de CIELab, Éste método requiere la determinación de dichos parámetros no solo en imágenes de ambos ojos sino también de las agallas. Como se ha mencionado anteriormente, la conclusión de éste método es que la tasa de error es muy alta, por tanto, este documento disuade al experto en la materia a utilizar únicamente parámetros de color de la imagen del ojo para evaluar la frescura del pescado.  In view of the most relevant prior art documents mentioned above, both individually and in combination, the present invention is not apparent. Muhamad et al. 2009, shows the determination of the freshness of the fish from images of both fish eyes based on the determination of the RGB parameters, and not of CIELab, This method requires the determination of these parameters not only in images of both eyes but also of the guts. As mentioned above, the conclusion of this method is that the error rate is very high, therefore, this document discourages the person skilled in the art to use only eye image color parameters to evaluate the freshness of the fish.
Por otra parte, aunque Mateo et al., 2006, muestra la determinación de los mismos parámetros que los usados en la presente invención, CIELab, las imágenes utilizadas no son de los ojos del pescado, y la enseñanza de dicho documento es que éstos parámetros permiten detectar la calidad y no la frescura del pescado, donde la calidad no viene definida solo por la frescura sino también por su contenido en grasas, el color externo y la ausencia de Ya/ce (término japonés de lo que se conoce como Burn Tuna Syndrome). Además dicho documento enseña que la técnica de análisis basada en estos parámetros debe ser usada en combinación con otras técnicas, tal como la consistente en un análisis estadístico de la co-ocurrencia de niveles de gris en los píxeles de la imagen.  On the other hand, although Mateo et al., 2006, shows the determination of the same parameters as those used in the present invention, CIELab, the images used are not from the eyes of the fish, and the teaching of said document is that these parameters allow to detect the quality and not the freshness of the fish, where the quality is not defined only by the freshness but also by its fat content, the external color and the absence of Ya / ce (Japanese term of what is known as Burn Tuna Syndrome). Furthermore, said document teaches that the analysis technique based on these parameters should be used in combination with other techniques, such as that consisting of a statistical analysis of the co-occurrence of gray levels in the pixels of the image.
En definitiva, a la vista de lo mostrado en el estado de la técnica, el experto en la materia no usaría solo los parámetros CIELab para determinar la frescura tal y como se muestra en la presente invención, y sobre todo no lo haría sobre únicamente imágenes oculares del pescado.  In short, in view of what is shown in the state of the art, the person skilled in the art would not only use the CIELab parameters to determine the freshness as shown in the present invention, and above all he would not do it on images only. Fish eyepieces.
Asimismo, las propuestas citadas también adolecen de la falta de sistemas de calibración adecuados que permitan a un usuario no experimentado determinar la calidad de un pescado para cuya variedad exista una base de datos almacenada en memoria. Referencias: Likewise, the aforementioned proposals also suffer from the lack of adequate calibration systems that allow an inexperienced user to determine the quality of a fish for whose variety there is a database stored in memory. References:
BOGDANOVIC T, Simat V, Frka-Roic A, Markovic K., Development and Application of Quality IndexMethodScheme in a Shelf-LifeStudy of Wild and Fish FarmAffected Bogue (Boopsboops, L). Journal of Food Science. Febrero 2012. Volúmen 77, Issue 2, páginas S99-S106. BOGDANOVIC T, Simat V, Frka-Roic A, Markovic K., Development and Application of Quality Index Method Method in a Shelf-LifeStudy of Wild and Fish Farm Protected Bogue (Boopsboops, L). Journal of Food Science. February 2012. Volume 77, Issue 2, pages S99-S106.
GÜMÜS, B, Balaban.M. Ó., Ünlüsayin, M. Machine VisionApplicationstoAquaticFoods: A Review. TurkishJournal of Fisheries and AquaticSciences 11 : 171-181.2011.  GÜMÜS, B, Balaban.M. Ó., Ünlüsayin, M. Machine VisionApplicationstoAquaticFoods: A Review. TurkishJournal of Fisheries and AquaticSciences 11: 171-181.2011.
- OLAFSDOTTIR, G, Nesvadba, P, Di Natale, C, Careche, M, Oehlenschláger, J, Tryggvadóttir, R, Schubring, R, Kroeger, M, Heia, K, Esaiassen, M, Macagnano, A, Jorgensen, B. 2004. "Multi sensor for fish quality determination". Trends in Food Science & Technology 15, páginas 86 a 93.  - OLAFSDOTTIR, G, Nesvadba, P, Di Natale, C, Careche, M, Oehlenschláger, J, Tryggvadóttir, R, Schubring, R, Kroeger, M, Heia, K, Esaiassen, M, Macagnano, A, Jorgensen, B. 2004. "Multi sensor for fish quality determination". Trends in Food Science & Technology 15, pages 86 to 93.
- HOSSEINI.H.G., Luo, D, Xu, G, Liu, H, Benjamín D. 2008. Intelligent Fish Freshness Assessment. Journal of Sensors.  - HOSSEINI.H.G., Luo, D, Xu, G, Liu, H, Benjamin D. 2008. Intelligent Fish Freshness Assessment. Journal of Sensors
MUHAMAD F; Hashim H; Jarmin R; Ahmad A., "Fish freshness classification based on image processing and fuzzy logic". Proceedings on the 8th WSEAS International Conference on Circuits, Systems, Electronics, Control and Signal Processing (CSECS 2009), 2009, páginas.109 a 115.  MUHAMAD F; Hashim H; Jarmin R; Ahmad A., "Fish freshness classification based on image processing and fuzzy logic". Proceedings on the 8th WSEAS International Conference on Circuits, Systems, Electronics, Control and Signal Processing (CSECS 2009), 2009, pages 109 to 115.
- MATEOA; Soto F; Villarejo J A; Roca-Dorda J; De la Gándara F; García A., "Quality analysis of tuna meat using an automated color inspection system", Aquacultural Engíneering, Junio 2006, vol. 35, páginasl a 13.  - MATEOA; Soto F; Villarejo J A; Rock-Dorda J; From Gándara F; García A., "Quality analysis of tuna meat using an automated color inspection system", Aquacultural Engíneering, June 2006, vol. 35, pages 1 to 13.
Explicación de la invención Explanation of the invention.
La presente invención aporta una alternativa al estado de la técnica que pretende mejorar los resultados obtenidos mediante las propuestas conocidas de determinación de la frescura del pescado basadas en el análisis de parámetros de color de imágenes oculares del mismo, tal como la descrita en el artículo "Fishfreshness classification based on image processing and fuzzylogic" cuyos pobres resultados son claramente mejorables.  The present invention provides an alternative to the state of the art that aims to improve the results obtained by the known proposals for determining the freshness of the fish based on the analysis of color parameters of ocular images thereof, as described in the article " Fishfreshness classification based on image processing and fuzzylogic "whose poor results are clearly improvable.
Para ello, la presente invención concierne a un procedimiento para determinar la frescura del pescado basado en el procesamiento de imágenes oculares, que comprende:  For this, the present invention concerns a method for determining the freshness of the fish based on the processing of ocular images, comprising:
a) la adquisición, bajo unas condiciones determinadas, de al menos una imagen del ojo de la muestra de un pescado objetivo; y b) la determinación y el procesamiento de uno o más parámetros de color de dicha imagen adquirida. a) the acquisition, under certain conditions, of at least one eye image of the sample of a target fish; Y b) the determination and processing of one or more color parameters of said acquired image.
A diferencia de las propuestas conocidas, en el procedimiento propuesto por el primer aspecto de la invención, de manera característica, la etapa b) comprende:  Unlike the known proposals, in the procedure proposed by the first aspect of the invention, in a characteristic manner, step b) comprises:
b1 ) el procesamiento de los datos crudos de la imagen adquirida y la segmentación de la imagen para fijar el parámetro o parámetros de color del ojo de la muestra del pescado objetivo;  b1) the processing of the raw data of the acquired image and the segmentation of the image to set the eye color parameter or parameters of the target fish sample;
b2) la determinación en la imagen de la etapa b1 ) de al menos uno de los parámetros L*, a* y/o b* del espacio CIELab y de su valor correspondiente; y b2) the determination in the image of step b1) of at least one of the parameters L * , a * and / or * of the CIELab space and its corresponding value; Y
b3) la interpolación del valor obtenido en la etapa b2) en como mínimo una curva de calibrado generada a partir de unos valores obtenidos con especímenes del mismo tipo, tras realizar una pluralidad de dichas etapas a), b1 ) y b2) para unas imágenes, adquiridas bajo dichas condiciones determinadas, de los ojos de distintas muestras de pescados de referencia de la especie a analizar, para diferentes valores de frescura.  b3) the interpolation of the value obtained in step b2) in at least one calibration curve generated from values obtained with specimens of the same type, after performing a plurality of said stages a), b1) and b2) for images , acquired under these determined conditions, from the eyes of different samples of reference fish of the species to be analyzed, for different freshness values.
El procedimiento comprende además una etapa c) de determinación de la frescura de la muestra del pescado objetivo a partir del valor interpolado en la etapa b3).  The method further comprises a step c) of determining the freshness of the sample of the target fish from the value interpolated in step b3).
En la presente invención, se entiende por frescura el tiempo transcurrido desde la captura del pescado durante el cual el pescado se ha mantenido refrigerado a 0°C o por debajo de 0°C sin alcanzar su punto de congelación (que en general es de unos - 1 ,5°C). La frescura puede ser expresada en días, meses, horas, o cualquier otra medida temporal. Preferiblemente, la frescura se expresa en días.  In the present invention, freshness is understood as the time elapsed since the capture of the fish during which the fish has been kept refrigerated at 0 ° C or below 0 ° C without reaching its freezing point (which in general is about - 1, 5 ° C). The freshness can be expressed in days, months, hours, or any other temporary measure. Preferably, the freshness is expressed in days.
Según un ejemplo de realización, el procedimiento comprende, en la etapa c), proporcionar el valor de la frescura determinada en términos de días en que el pescado se ha mantenido a 0 grados o por debajo de 0°C sin alcanzar su punto de congelación.  According to an embodiment, the process comprises, in step c), providing the value of the freshness determined in terms of days when the fish has been kept at 0 degrees or below 0 ° C without reaching its freezing point .
La curva de calibrado, según un ejemplo de realización, es una curva que relaciona al menos uno de los parámetros L*, a* y/o b* con días en que el pescado se ha mantenido a 0 grados o por debajo de 0°C sin alcanzar su punto de congelación.  The calibration curve, according to an embodiment example, is a curve that relates at least one of the parameters L *, to * and / or * with days when the fish has been kept at 0 degrees or below 0 ° C without reaching its freezing point.
El procedimiento comprende, para unos ejemplos de realización, determinar en la etapa b2) varios de los parámetros indicados, y utilizar, en la etapa b3), varias curvas de calibrado referentes a dichos parámetros.  The method comprises, for some embodiments, determining in step b2) several of the indicated parameters, and using, in step b3), several calibration curves referring to said parameters.
Para otro ejemplo de realización, el procedimiento comprende utilizar en la etapa b3) curvas de calibrado referentes a combinaciones obvias de los parámetros citados, tal como L*+a*, a*- b*, etc., e interpolar los valores de los parámetros determinados en la etapa b2) tras combinarlos de la misma manera.  For another exemplary embodiment, the method comprises using in step b3) calibration curves referring to obvious combinations of the mentioned parameters, such as L * + a *, a * - b *, etc., and interpolating the values of the parameters determined in step b2) after combining them in the same way.
Preferentemente, las etapas b1 ), b2), b3) y c) se realizan automáticamente. Para un ejemplo de realización preferido, la etapa b) se realiza sobre la parte de la imagen adquirida correspondiente al iris del ojo del pescado. Preferably, steps b1), b2), b3) and c) are performed automatically. For a preferred embodiment, step b) is performed on the part of the acquired image corresponding to the iris of the fish's eye.
Para un ejemplo de realización el procedimiento comprende generar y almacenar en memoria como mínimo dicha curva de calibrado.  For an exemplary embodiment, the method comprises generating and storing at least said calibration curve.
Esta idea de la calibración y su almacenamiento en memoria no resulta evidente, a partir de las propuestas conocidas, para conseguir un sistema de determinación rápida de la frescura del pescado a través, exclusivamente, del tratamiento de imágenes, con preferencia digitales, obtenidas por personal no especializado.  This idea of calibration and its storage in memory is not evident, from the known proposals, to achieve a system of rapid determination of the freshness of the fish through exclusively the treatment of images, preferably digital, obtained by personnel Not specialized
Por lo que se refiere al almacenamiento en memoria de la curva de calibrado, éste hace referencia al almacenamiento en cualquier clase de memoria o dispositivo equivalente conocido, ya sea en un sistema local o bien en uno remoto, o una combinación de los mismos.  As regards the storage in memory of the calibration curve, it refers to storage in any kind of memory or equivalent device known, either in a local system or in a remote one, or a combination thereof.
El procedimiento del primer aspecto de la invención permite la medida rápida de la frescura del pescado sin utilizar un panel entrenado de catadores ni métodos instrumentales. El procedimiento permite la determinación de la frescura del pescado a partir exclusivamente del procesamiento de diferentes parámetros de imágenes digitales (fotos) que se comparan con una biblioteca de datos.  The process of the first aspect of the invention allows the rapid measurement of the freshness of the fish without using a trained panel of tasters or instrumental methods. The procedure allows the determination of the freshness of the fish based exclusively on the processing of different parameters of digital images (photos) that are compared with a data library.
Generalmente la apariencia de los ojos tiene buena relación con la frescura del pescado. Algunos de los factores que se consideran en la apariencia de los ojos son claridad, oscuridad, color y concentración de color. En el procedimiento de la presente invención se emplean imágenes de los ojos de los especímenes y mediante el procesamiento de la imagen digital se determina la frescura del pescado empleando parámetros simples y/o combinaciones de ellos.  Generally the appearance of the eyes has a good relationship with the freshness of the fish. Some of the factors that are considered in the appearance of the eyes are clarity, darkness, color and color concentration. In the process of the present invention images of the eyes of the specimens are used and by means of the digital image processing the freshness of the fish is determined using simple parameters and / or combinations thereof.
La imagen adquirida es una imagen digital obtenida mediante una cámara digital, en condiciones determinadas que incluyen utilizar una distancia entre el ojo del pescado y la lente de la cámara en un intervalo entre 10-30 cm y utilizar una fuente de iluminación de entre 2500 y 6500 grados Kelvin de temperatura de color.  The acquired image is a digital image obtained by a digital camera, under certain conditions that include using a distance between the fish's eye and the camera lens in a range between 10-30 cm and using a lighting source between 2500 and 6500 Kelvin degrees of color temperature.
Para un ejemplo de realización preferido, los valores mediante los cuales se ha generado dicha curva de calibrado han sido obtenidos para unas imágenes de los ojos de las distintas muestras de pescados de referencia mantenidas a una temperatura de 0 grados Celsius o ligeramente por debajo de ésta.  For a preferred embodiment, the values by which said calibration curve has been generated have been obtained for images of the eyes of the different samples of reference fish kept at a temperature of 0 degrees Celsius or slightly below this .
Para un ejemplo de realización, el procesamiento de los datos crudos de la imagen de la etapa b1 ) incluye un pre-procesado o procesamiento inicial de los datos crudos de la imagen adquirida en la etapa a) para la corrección de deformaciones geométricas, eliminación de ruido, corrección del nivel de grises y corrección del enturbiado. For an exemplary embodiment, the processing of the raw data of the image of step b1) includes a preprocessing or initial processing of the raw data of the image acquired in step a) for the correction of deformations geometric, noise elimination, gray level correction and cloud correction.
El procedimiento comprende, de acuerdo con un ejemplo de realización:  The method comprises, according to an embodiment example:
- realizar dicha segmentación de la etapa b1 ) sobre la imagen pre-procesada en una pluralidad de áreas de interés para fijar los parámetros de color con respecto al iris del ojo de la muestra de pescado;  - performing said segmentation of step b1) on the pre-processed image in a plurality of areas of interest to set the color parameters with respect to the iris of the eye of the fish sample;
- realizar una etapa de reconocimiento del ojo del pescado centrando la imagen sobre el mismo; y  - perform a stage of recognition of the eye of the fish centering the image on it; Y
- realizar la etapa b2) sobre dicha imagen centrada sobre el ojo del pescado. El método comprende, de acuerdo con un ejemplo de realización, comparar, de manera manual o automática, el valor de frescura determinado en la etapa c) con el valor de frescura real de la muestra del pescado objetivo para verificar si se ha mantenido la cadena de frío.  - perform stage b2) on said image centered on the fish's eye. The method comprises, according to an embodiment example, comparing, manually or automatically, the freshness value determined in step c) with the actual freshness value of the sample of the target fish to verify whether the chain has been maintained of cold.
De acuerdo con un ejemplo de realización, el procedimiento del primer aspecto de la invención comprende:  According to an exemplary embodiment, the process of the first aspect of the invention comprises:
i) adquirir, un usuario, una imagen del ojo de la muestra del pescado objetivo bajo dichas condiciones determinadas, mediante un dispositivo de computación portátil con cámara digital y capacidad de comunicaciones;  i) acquire, a user, an image of the eye of the sample of the target fish under said determined conditions, by means of a portable computing device with digital camera and communications capability;
ii) enviar, dicho usuario, dicha imagen adquirida o información asociada a ia misma, desde dicho dispositivo de computación portátil hasta un dispositivo de computación remoto con acceso a la curva o curvas de calibrado;  ii) sending said user, said acquired image or information associated therewith, from said portable computing device to a remote computing device with access to the calibration curve or curves;
iii) realizar, por parte del dispositivo de computación remoto, al menos dichas etapas b3) y c); y  iii) perform, by the remote computing device, at least said steps b3) and c); Y
¡v) enviar, desde el dispositivo de computación remoto hasta el dispositivo de computación portátil, el valor de frescura determinado en la etapa c).  V) send, from the remote computing device to the portable computing device, the freshness value determined in step c).
Según una variante de dicho ejemplo de realización, la etapa ii) comprende enviar la imagen adquirida y la etapa iii) comprende realizar también, por parte del dispositivo de computación remoto, las etapas b1 ) y b2).  According to a variant of said exemplary embodiment, step ii) comprises sending the acquired image and step iii) also comprises carrying out, by the remote computing device, steps b1) and b2).
Según una variante alternativa, el procedimiento comprende realizar las etapas b1 ) y b2) por parte del dispositivo de computación portátil, y la etapa ii) comprende enviar dicha información asociada a la imagen adquirida, siendo dicha información el valor o valores determinados en la etapa b2).  According to an alternative variant, the method comprises performing steps b1) and b2) by the portable computing device, and stage ii) comprises sending said information associated with the acquired image, said information being the value or values determined in the stage b2).
Según un ejemplo de realización, el procedimiento comprende, de manera previa a dicha etapa iii), enviar, el usuario, desde el dispositivo de computación portátil hasta el dispositivo de computación remoto, junto con el envío de la imagen, o de manera previa o posterior, una señal indicando la especie a la cual pertenece la muestra de pescado objetivo, con el fin de que se realice la etapa b3) sobre curvas de calibración relativas a dicha especie. According to an exemplary embodiment, the method comprises, prior to said stage iii), sending, the user, from the portable computing device to the remote computing device, together with the sending of the image, or prior or later, a signal indicating the species to which the sample of target fish, in order to perform step b3) on calibration curves related to that species.
De acuerdo con otro ejemplo de realización, el procedimiento propuesto por el primer aspecto de la invención comprende realizar las etapas descritas para una pluralidad de pescados objetivos de manera simultánea, incluyendo la imagen adquirida datos de imagen referentes a los ojos de dicha pluralidad de pescados objetivo.  According to another embodiment, the method proposed by the first aspect of the invention comprises performing the steps described for a plurality of objective fish simultaneously, including the image acquired image data relating to the eyes of said plurality of target fish. .
El método del primer aspecto de la invención incluye una calibración tal que permite la determinación rápida de la frescura del pescado a través, exclusivamente, del tratamiento de imágenes digitales obtenidas por personal no especializado.  The method of the first aspect of the invention includes a calibration such that it allows the rapid determination of the freshness of the fish through exclusively the treatment of digital images obtained by non-specialized personnel.
Un segundo aspecto de la invención concierne a un sistema para determinar la frescura del pescado basado en el procesamiento de imágenes oculares, configurado para implementar el procedimiento del primer aspecto, y que comprende:  A second aspect of the invention concerns a system for determining the freshness of the fish based on the processing of ocular images, configured to implement the procedure of the first aspect, and comprising:
- medios de adquisición de imágenes para realizar la etapa a) del procedimiento; y  - means of acquiring images to perform step a) of the procedure; Y
- un sistema electrónico, en conexión con dichos medios de adquisición de imágenes para recibir las imágenes adquiridas, y que está configurado para implementar la etapa b).  - an electronic system, in connection with said image acquisition means to receive the acquired images, and which is configured to implement step b).
El sistema electrónico está configurado para implementar las etapas b1), b2), b3) y c) del procedimiento, comprendiendo o teniendo acceso a como mínimo una memoria donde se encuentra registrada la curva o curvas de calibrado para realizar la etapa b3).  The electronic system is configured to implement steps b1), b2), b3) and c) of the procedure, comprising or having access to at least one memory where the calibration curve or curves are registered to perform step b3).
Para la variante para la cual el sistema electrónico no comprende pero sí que tiene acceso a dicha memoria, ésta puede estar ubicada en cualquier clase de sistema remoto, tal como el conocido comúnmente como "nube", y acceder al mismo mediante cualquier tipo de red de comunicaciones.  For the variant for which the electronic system does not understand but does have access to said memory, it can be located in any kind of remote system, such as commonly known as "cloud", and access it through any type of network of communications.
De acuerdo con un ejemplo de realización del sistema propuesto por el segundo aspecto de la invención, los medios de adquisición de imágenes comprenden:  According to an embodiment of the system proposed by the second aspect of the invention, the image acquisition means comprise:
- una cámara digital, como dispositivo independiente o dispuesta, por ejemplo, en un teléfono móvil inteligente u otra clase de dispositivo portador de una cámara; y - un dispositivo auxiliar separador a disponer entre la lente de la cámara digital y el ojo del pescado cuya imagen se desea adquirir, que está formado por un cuerpo de material no transparente de entre 10-30 cm de altura con un orificio longitudinal pasante para comunicar lumínicamente a ambos, la lente de la cámara y el ojo del pescado, cuando se dispone entre ambos. Según un ejemplo de realización, el dispositivo auxiliar separador comprende unos medios de iluminación dispuestos y configurados para iluminar a dicho ojo del pescado a través del orificio longitudinal de dicho cuerpo. - a digital camera, as a stand-alone device or arranged, for example, in a smart mobile phone or other kind of device carrying a camera; and - an auxiliary separating device to be disposed between the lens of the digital camera and the eye of the fish whose image is to be acquired, which is formed by a body of non-transparent material between 10-30 cm high with a through hole for Lightly communicate both the camera lens and the fish's eye when it is arranged between them. According to an exemplary embodiment, the auxiliary separating device comprises lighting means arranged and configured to illuminate said fish eye through the longitudinal hole of said body.
Para una implementación de dicho ejemplo de realización, los medios de iluminación comprenden una fuente de luz introducida, al menos parcialmente, en un orificio transversal pasante realizado en una pared del cuerpo, para iluminar el interior del orificio longitudinal.  For an implementation of said exemplary embodiment, the lighting means comprise a light source introduced, at least partially, into a transverse through hole made in a wall of the body, to illuminate the interior of the longitudinal hole.
Con preferencia dicho orificio transversal pasante tiene un diámetro de entre 2 a 5 cm y se encuentra ubicado a una altura de entre 2,5 a 7,5 cm desde la base del cuerpo a disponer sobre el pescado.  Preferably said through transverse hole has a diameter of between 2 to 5 cm and is located at a height of between 2.5 to 7.5 cm from the base of the body to be arranged on the fish.
Para un ejemplo de realización, el sistema está adaptado para implementar el anteriormente descrito ejemplo de realización del procedimiento del primer aspecto que referente a la realización de las etapas i) a ¡v), y que comprende:  For an exemplary embodiment, the system is adapted to implement the aforementioned exemplary embodiment of the procedure of the first aspect which refers to the realization of steps i) to v), and which comprises:
- un dispositivo de computación portátil (tal como un teléfono inteligente, una PDA, etc.) con capacidad de comunicaciones, con preferencia inalámbricas, que incluye a dicha cámara digital y a una parte local de dicho sistema electrónico para implementar las etapas i) y ii) del procedimiento del primer aspecto; y  - a portable computing device (such as a smartphone, a PDA, etc.) with communications capability, preferably wireless, that includes said digital camera and a local part of said electronic system to implement stages i) and ii ) of the first aspect procedure; Y
- un dispositivo de computación remoto con capacidad de comunicaciones, con preferencia inalámbrica, que incluye a una parte remota de dicho sistema electrónico para implementar las etapas iii) y iv) del procedimiento.  - a remote computing device with communications capability, preferably wireless, that includes a remote part of said electronic system to implement steps iii) and iv) of the procedure.
Con el fin de mantener las mismas condiciones determinadas para la adquisición de la imagen de la muestra de pescado objetivo bajo las cuales se han adquirido las imágenes de las muestras de pescado de referencia, el sistema propuesto por el segundo aspecto de la invención también comprende al dispositivo auxiliar separador descrito anteriormente, a utilizar junto con el dispositivo de computación portátil para implementar la etapa i).  In order to maintain the same conditions determined for the acquisition of the image of the target fish sample under which the images of the reference fish samples have been acquired, the system proposed by the second aspect of the invention also comprises the auxiliary separator device described above, to be used together with the portable computing device to implement step i).
En general, el dispositivo de computación portátil dispone de una pantalla donde mostrar el valor de frescura recibido en la etapa iv).  In general, the portable computing device has a screen to show the freshness value received in stage iv).
Un tercer aspecto de la invención concierne a un programa de ordenador adaptado para ejecutar el procedimiento del primer aspecto, incluyendo la realización de las etapa b1), b2), b3) y c).  A third aspect of the invention concerns a computer program adapted to execute the procedure of the first aspect, including performing steps b1), b2), b3) and c).
Según un ejemplo de realización, el programa de ordenador comprende una primera aplicación de software ejecutable por parte del dispositivo de computación portátil y una segunda aplicación de software ejecutable por parte del servidor remoto, llevándose a cabo, entre ambas aplicaciones, las anteriormente descritas etapa ii) a iv). Según un ejemplo de realización, la primera aplicación de software permite al usuario realizar la selección de la especie a la cual pertenece la muestra de pescado objetivo, que hará que el dispositivo de computación envíe la señal indicativa correspondiente al dispositivo de computación remoto. According to an exemplary embodiment, the computer program comprises a first executable software application by the portable computing device and a second executable software application by the remote server, being carried out, between both applications, the previously described stage ii ) to iv). According to an exemplary embodiment, the first software application allows the user to make the selection of the species to which the target fish sample belongs, which will cause the computing device to send the corresponding signal signal to the remote computing device.
Breve descripción de los dibujos Brief description of the drawings
Las anteriores y otras ventajas y características se comprenderán más plenamente a partir de la siguiente descripción detallada de unos ejemplos de realización con referencia a los dibujos adjuntos, que deben tomarse a título ilustrativo y no limitativo, en los que:  The foregoing and other advantages and features will be more fully understood from the following detailed description of some embodiments with reference to the attached drawings, which should be taken by way of illustration and not limitation, in which:
las Figs. 1 , 2 y 3 muestran una curvas de calibrado en función de, respectivamente, los parámetros L*, a* y b*, generadas y utilizadas de acuerdo con el procedimiento propuesto por el primer aspecto de la invención, para unos ejemplos de realización;  Figs. 1, 2 and 3 show a calibration curve based on, respectively, the parameters L *, a * and b *, generated and used in accordance with the procedure proposed by the first aspect of the invention, for some examples of embodiment;
la Fig. 4 muestra la evolución temporal del parámetro ΔΕ calculado para los valores mostrados en las curvas de las Figs. 1 a 3 respecto a unos valores iniciales. la Fig. 5 es una gráfica que muestra los cambios que experimenta el parámetro L* en función de la conservación del pescado, para diferentes condiciones térmicas de almacenamiento, para tres pescados de muestra, dos de los cuales son pescados deteriorados debido a que se ha roto la cadena del frío para ellos;  Fig. 4 shows the temporal evolution of the parameter ΔΕ calculated for the values shown in the curves of Figs. 1 to 3 regarding initial values. Fig. 5 is a graph that shows the changes that the L * parameter undergoes in terms of fish conservation, for different thermal storage conditions, for three sample fish, two of which are deteriorated fish because it has been broken the cold chain for them;
las Figs. 6 y 7 son sendas gráficas análogas a la de la Fig. 5 pero con relación a, respectivamente, la variación del parámetro a* y del parámetro b*; y Figs. 6 and 7 are graphical paths analogous to that of Fig. 5 but in relation to, respectively, the variation of parameter a * and parameter b * ; Y
la Fig. 8 es una vista esquemática en perspectiva de los medios de adquisición de imágenes del sistema propuesto por el segundo aspecto de la invención, para un ejemplo de realización.  Fig. 8 is a schematic perspective view of the image acquisition means of the system proposed by the second aspect of the invention, for an exemplary embodiment.
Descripción detallada de unos ejemplos de realización Detailed description of some embodiments
El procedimiento del primer aspecto de la invención comprende, para un ejemplo de realización, un primer paso E1 de adquisición de imagen. Se toma una imagen digital de los ojos del pescado en unas condiciones muy específicas: distancia entre el ojo de pescado y la lente de la cámara en un intervalo entre 10 y 30 cm, con una iluminación controlada del orden de 2500- 6500 grados Kelvin. Estas condiciones se pueden conseguir mediante un dispositivo cilindrico o cónico abierto por sus extremos, fabricado en un material no transparente y blanco, de entre 10-30 cm de altura, con un orificio de 2-5 cm de diámetro, situado a una altura entre 2,5-7,5 cm desde la base y una fuente de luz fluorescente o de LEDs, tal y como el ilustrado en la Fig. 8, que se describirá posteriormente con referencia al sistema propuesto por el segundo aspecto de la invención. The method of the first aspect of the invention comprises, for an exemplary embodiment, a first image acquisition step E1. A digital image of the fish's eyes is taken in very specific conditions: distance between the fish eye and the camera lens in an interval between 10 and 30 cm, with a controlled illumination of the order of 2500-6500 degrees Kelvin. These conditions can be achieved by a cylindrical or conical device open at its ends, made of a non-transparent and white material, between 10-30 cm high, with a hole of 2-5 cm in diameter, located at a height between 2.5-7.5 cm from the base and a fluorescent or LED light source, as illustrated in Fig. 8, which is will describe later with reference to the system proposed by the second aspect of the invention.
La adquisición de la imagen se plasma en la transferencia de la señal electrónica del dispositivo fotográfico en forma numérica y permite, tras un pre- procesado, o etapa E2, establecer unos parámetros que son los que se emplearán para evaluar la frescura del pescado.  The acquisition of the image is reflected in the transfer of the electronic signal of the photographic device in numerical form and allows, after a preprocessing, or step E2, to establish parameters that are those that will be used to evaluate the freshness of the fish.
El pre-procesado de la imagen E2 se refiere al procesamiento inicial de los datos crudos de imagen para la corrección de deformaciones geométricas, la eliminación de ruido, corrección del nivel de grises y la corrección del enturbiado.  The preprocessing of the E2 image refers to the initial processing of the raw image data for the correction of geometric deformations, the elimination of noise, the gray level correction and the clouding correction.
La segmentación de la imagen, o etapa E3, permite dividirla en las regiones que tienen una gran correlación con los objetos o áreas de interés. En el presente caso, se trata de fijar los parámetros del iris del ojo de la muestra.  The segmentation of the image, or stage E3, allows it to be divided into regions that have a great correlation with the objects or areas of interest. In the present case, it is about setting the iris parameters of the sample eye.
Tras la etapa E3 se realiza una etapa E4 de reconocimiento del ojo del pescado centrando la imagen sobre el mismo, y tras ésta se determinan en el iris los parámetros: L*, a* y/o b*, en una etapa E5 de extracción de parámetros, que permiten correlacionar las imágenes con la frescura del pescado en el espacio CIE L*a*b* (CIELAB), que es el modelo de color más completo convencionalmente usado para describir todos los colores visibles al ojo humano. Fue desarrollado para este propósito específico por la Comisión Internacional de Iluminación. Los tres parámetros básicos utilizados en el modelo utilizado representan la claridad del color (L*, L*=0 indica negro y L*=100 indica blanco), su posición entre rojo y verde (a*, valores negativos indican valores desplazados hacia el verde mientras que valores positivos indican la proximidad al rojo) y su posición entre amarillo y azul (b*, valores negativos indican valores azules y positivos indican amarillo). After stage E3 a stage E4 of recognition of the fish eye is carried out centering the image on it, and after this the parameters are determined in the iris: L *, a * and / ob *, in a stage E5 of extraction of parameters, which allow the images to be correlated with the freshness of the fish in the CIE L * a * b * (CIELAB) space, which is the most complete color model conventionally used to describe all colors visible to the human eye. It was developed for this specific purpose by the International Lighting Commission. The three basic parameters used in the model used represent the clarity of color (L * , L * = 0 indicates black and L * = 100 indicates white), its position between red and green (a * , negative values indicate values shifted towards the green while positive values indicate proximity to red) and its position between yellow and blue (b * , negative values indicate blue values and positive values indicate yellow).
La siguiente etapa del procedimiento, o etapa E6, es la interpolación de los parámetros de color en la curva de calibrado previamente establecida con muestras de referencia, de la misma especie de la que se va a evaluar, para determinar la frescura (definida como días transcurridos desde la muerte del pescado, habiéndose conservado éste a cero grados centígrados). La determinación puede realizarse usando un único parámetro de color o combinaciones de los mismos.  The next stage of the procedure, or stage E6, is the interpolation of the color parameters in the previously established calibration curve with reference samples, of the same species to be evaluated, to determine the freshness (defined as days elapsed since the death of the fish, having kept it at zero degrees Celsius). The determination can be made using a single color parameter or combinations thereof.
El calibrado se ha construido previamente a partir de una biblioteca de imágenes de pescados de muestra, que es diferente para cada especie, y que se tomaron en unas condiciones de iluminación determinadas que deben ser mantenidas fijas en todas las nuevas medidas para obtener una determinación correcta. Las curvas de calibrado a utilizar según el procedimiento propuesto por el primer aspecto de la invención (individualmente o en combinación) se muestran en las Figs. 1 a 3 para, respectivamente, los parámetros L*, a* y b*. The calibration has been previously constructed from a library of images of sample fish, which is different for each species, and that were taken under certain lighting conditions that must be kept fixed in all new measures to obtain a correct determination . The calibration curves to be used according to the procedure proposed by the first aspect of the invention (individually or in combination) are shown in Figs. 1 to 3 for, respectively, the parameters L *, a * and b *.
En la Fig. 4 se muestra una curva relativa al parámetro ΔΕ. Éste es un parámetro relativo a la diferencia de color total, que tiene en cuenta las diferencias individuales entre el valor de cada parámetro L*, a* y b* en función del tiempo y el valor de cada uno tomado a tiempo cero; esto es, el valor de cada parámetro obtenido para cada día transcurrido, y el valor de partida para un tiempo cero (pescado recién muerto), y se utiliza para verificar la independencia de las curvas de calibrado obtenidas para los parámetros L*, a* y b*. A curve relative to the parameter ΔΕ is shown in Fig. 4. This is a parameter relative to the total color difference, which takes into account the individual differences between the value of each parameter L * , a * and b * as a function of time and the value of each taken at zero time; that is, the value of each parameter obtained for each elapsed day, and the starting value for a zero time (freshly killed fish), and is used to verify the independence of the calibration curves obtained for the parameters L *, a * and b *.
Hay varias fórmulas para el cálculo de ΔΕ*, siendo la más común y sencilla de implementar la CIE76: There are several formulas for the calculation of ΔΕ * , being the most common and simple to implement ICD76:
ΔΕ* = ((L*¡ - L* 0)2 + (a*, - a* 0)2 + (b*¡ - b* 0)2)1'2 donde los subíndices i y 0 se refieren, respectivamente, a los valores tomados para cada día transcurrido y a los tomados a tiempo cero. ΔΕ * = ((L * ¡- L * 0 ) 2 + (a * , - a * 0 ) 2 + (b * ¡- b * 0 ) 2 ) 1 ' 2 where the subscripts i and 0 refer respectively to the values taken for each day elapsed and those taken at zero time.
Finalmente, en la etapa E7, se realiza una clasificación del pescado a partir de la frescura determinada como resultado de la etapa E6.  Finally, in stage E7, a classification of the fish is made based on the freshness determined as a result of stage E6.
Según un ejemplo de realización, el reconocimiento del ojo, así como todas las etapas de procesamiento de la imagen, extracción de parámetros y extrapolación en el calibrado se llevan a cabo empleando un software desarrollado en entorno MATLAB.  According to an exemplary embodiment, the eye recognition, as well as all the stages of image processing, parameter extraction and extrapolation in the calibration are carried out using software developed in MATLAB environment.
Tal y como se ha descrito en un apartado anterior, el procedimiento propuesto por el primer aspecto de la invención también sirve, para unos ejemplos de realización, como método de control de la trazabilidad térmica del pescado, es decir, para detectar cambios en el mantenimiento/almacenamiento del pescado. Para demostrar esto, se ha llevado a cabo el estudio de la evolución de los parámetros de imagen de los ojos de ejemplares de dorada que se habían conservado durante un tiempo a temperatura ambiente (25°C) con el fin de comprobar los efectos de romper la cadena de frío (0°C) sobre la frescura del pescado.  As described in a previous section, the procedure proposed by the first aspect of the invention also serves, for some examples of embodiment, as a method of controlling the thermal traceability of fish, that is, to detect changes in maintenance / fish storage. To demonstrate this, the study of the evolution of the image parameters of the eyes of gilthead specimens that had been preserved for a time at room temperature (25 ° C) has been carried out in order to verify the effects of breaking the cold chain (0 ° C) on the freshness of the fish.
Las figuras 5 a 7 evidencian para tres ejemplares objeto de estudio (indicados como P1 , P2 y P3) que la rotura de la cadena de frío afecta a los parámetros de las imágenes, denunciando un estado de frescura equivalente a un aumento del tiempo de almacenamiento. Es de destacar que este efecto se evidencia mediante los parámetros L*, a* y/o b*; pudiéndose obtener mejoras en la detección de la interrupción de la cadena de frío usando productos o cocientes de los parámetros anteriores. En concreto, las curvas ¡lustradas en las Figs. 5 a 7 muestran los cambios que experimentan los parámetros L*,a* y b*en función de la conservación del pescado, para diferentes condiciones térmicas de almacenamiento, a lo largo de cinco días (indicados como d1 a d5) para tres pescados de muestra P1 , P2 y P3, y han sido creadas a partir de unos datos de referencia obtenidos a su vez a partir de los valores obtenidos tras realizar una pluralidad de etapas a), b1 ), b2, b3) y c) sobre unas imágenes adquiridas de los ojos de los pescados de muestra P1 , P2, P3, para diferentes grados de temperatura de conservación a lo largo del tiempo. Figures 5 to 7 show for three specimens under study (indicated as P1, P2 and P3) that the breaking of the cold chain affects the parameters of the images, denouncing a state of freshness equivalent to an increase in storage time . It is noteworthy that this effect is evidenced by the parameters L *, a * and / ob *; being able to obtain improvements in the detection of the interruption of the cold chain using products or quotients of the previous parameters. Specifically, the curves illustrated in Figs. 5 to 7 show the changes that the L *, a * and b * parameters undergo fish conservation, for different thermal storage conditions, over five days (indicated as d1 to d5) for three sample fish P1, P2 and P3, and have been created from reference data obtained in turn from the values obtained after performing a plurality of stages a), b1), b2, b3) and c) on images acquired from The eyes of the sample fish P1, P2, P3, for different degrees of conservation temperature over time.
Los pescados P2 y P3 son pescados deteriorados debido a que su cadena del frío ha sido rota en uno u otro momento. En cambio el pescado P1 se ha conservado a 0o centígrados desde el momento inicial hasta el día 5, por lo que es un pescado considerado como fresco. Fish P2 and P3 are damaged fish because their cold chain has been broken at one time or another. On the other hand, P1 fish has been kept at 0 or Celsius from the initial moment until day 5, so it is a fish considered fresh.
En particular, el pescado de muestra P3 se ha conservado a cero grados en los periodos dO a d1 (es decir durante el primer día de almacenamiento desde la pesca del mismo), d1 a d1+8h y d3 a d5, y a 25 grados en los periodos d1+8h a d2 y d2 a d3, y el pescado P2 se ha mantenido a cero grados para todos los periodos indicados a excepción del que va desde d1+8h a d2.  In particular, the sample fish P3 has been kept at zero degrees in the periods dO to d1 (that is, during the first day of storage since fishing), d1 to d1 + 8h and d3 to d5, and 25 degrees in periods d1 + 8h to d2 and d2 to d3, and fish P2 has been maintained at zero degrees for all periods indicated except for the period from d1 + 8h to d2.
Estas curvas, o los datos incluidos en las mismas, pueden utilizarse para interpolar los valores de los parámetros medidos sobre los iris en las curvas de calibración, con el fin de confirmar que, en el caso de P2 y P3, los valores de frescura obtenidos son peores que los indicados en las etiquetas puesto que se han deteriorado debido a que se conservaron de forma inapropiada, es decir no se han mantenido a cero grados durante todo el período de conservación.  These curves, or the data included in them, can be used to interpolate the values of the parameters measured on the iris in the calibration curves, in order to confirm that, in the case of P2 and P3, the freshness values obtained they are worse than those indicated on the labels since they have deteriorated because they were improperly preserved, that is, they have not been maintained at zero degrees during the entire conservation period.
En la Fig. 8 se ilustra una implementación del sistema propuesto por el segundo aspecto de la invención, para un ejemplo de realización para el que éste comprende:  An implementation of the system proposed by the second aspect of the invention is illustrated in Fig. 8, for an exemplary embodiment for which it comprises:
- un dispositivo de computación portátil M con capacidad de comunicaciones, que incluye a una cámara digital C con una lente L y a una parte local del sistema electrónico (no ilustrada) para implementar las etapas i) y ii);  - a portable computing device M with communications capability, which includes a digital camera C with a lens L and a local part of the electronic system (not illustrated) to implement steps i) and ii);
- un dispositivo auxiliar separador D a disponer entre la lente L de la cámara digital C y el ojo del pescado (no ilustrado) cuya imagen se desea adquirir, que está formado por un cuerpo B de material no transparente de entre 10-30 cm de altura con un orificio longitudinal pasante 01 , de eje geométrico E, para comunicar lumínicamente a ambos, la lente L de la cámara C y el ojo del pescado, cuando se dispone entre ambos; y - un dispositivo de computación remoto SR con capacidad de comunicaciones, que incluye a una parte remota de dicho sistema electrónico (no ilustrada) para implementar las etapas iii) y iv). - an auxiliary separator device D to be disposed between the lens L of the digital camera C and the fish eye (not illustrated) whose image is to be acquired, which is formed by a body B of non-transparent material between 10-30 cm of height with a longitudinal through hole 01, of geometric axis E, to lightly communicate both the lens L of the chamber C and the eye of the fish, when disposed between them; Y - a remote computing device SR with communications capability, which includes a remote part of said electronic system (not illustrated) to implement stages iii) and iv).
El orificio transversal pasante 02 tiene, con preferencia, un diámetro de entre 2 a 5 cm y se encuentra ubicado a una altura de entre 2,5 a 7,5 cm desde la base del cuerpo B a disponer sobre el pescado, es decir desde la base inferior según la posición ilustrada en la Fig. 8.  The transverse through hole 02 preferably has a diameter between 2 to 5 cm and is located at a height between 2.5 to 7.5 cm from the base of the body B to be arranged on the fish, that is to say from the lower base according to the position illustrated in Fig. 8.
Si bien el dispositivo auxiliar separador D se ha descrito y reivindicado como parte de los medios de adquisición del sistema propuesto por el segundo aspecto de la invención, éste podría ser objeto de protección independiente para la aplicación aquí descrita u otras aplicaciones que requieran de las condiciones de adquisición de imágenes, especialmente en cuanto a distancia entre la lente y el objeto a fotografiar, requeridas por la aplicación referente al procedimiento propuesto por el primer aspecto de la presente invención.  Although the separating auxiliary device D has been described and claimed as part of the means of acquiring the system proposed by the second aspect of the invention, it could be object of independent protection for the application described herein or other applications that require the conditions of image acquisition, especially in terms of distance between the lens and the object to be photographed, required by the application referring to the procedure proposed by the first aspect of the present invention.
Un experto en la materia podría introducir cambios y modificaciones en los ejemplos de realización descritos sin salirse del alcance de la invención según está definido en las reivindicaciones adjuntas.  A person skilled in the art could introduce changes and modifications in the described embodiments without departing from the scope of the invention as defined in the appended claims.

Claims

Reivindicaciones Claims
1. - Procedimiento para determinar la frescura del pescado basado en el procesamiento de imágenes oculares, del tipo que comprende:  1. - Procedure for determining the freshness of the fish based on the processing of ocular images, of the type comprising:
a) la adquisición, bajo unas condiciones determinadas, de al menos una imagen del ojo de la muestra de un pescado objetivo; y  a) the acquisition, under certain conditions, of at least one eye image of the sample of a target fish; Y
b) la determinación y el procesamiento de al menos un parámetro de color de dicha imagen adquirida, que es al menos una,  b) the determination and processing of at least one color parameter of said acquired image, which is at least one,
estando dicho procedimiento caracterizado porque: said procedure being characterized in that:
dicha etapa b) comprende: said step b) comprises:
b1 ) el procesamiento de los datos crudos de la imagen adquirida y la segmentación de la imagen para fijar el parámetro o parámetros de color del ojo de la muestra del pescado objetivo;  b1) the processing of the raw data of the acquired image and the segmentation of the image to set the eye color parameter or parameters of the target fish sample;
b2) la determinación en la imagen de la etapa b1 ) de al menos uno de los parámetros L*, a* y/o b* del espacio CIELab, y de su valor correspondiente; y b2) the determination in the image of step b1) of at least one of the parameters L * , a * and / or * of the CIELab space, and their corresponding value; Y
b3) la interpolación del valor obtenido en la etapa b2) en al menos una curva de calibrado generada a partir de unos valores obtenidos tras realizar una pluralidad de dichas etapas a), b1 ) y b2) para unas imágenes, adquiridas bajo dichas condiciones determinadas, de los ojos de distintas muestras de pescados de referencia de la especia a analizar, para diferentes valores de frescura;  b3) the interpolation of the value obtained in step b2) in at least one calibration curve generated from values obtained after performing a plurality of said stages a), b1) and b2) for images, acquired under said determined conditions , from the eyes of different samples of reference fish of the spice to be analyzed, for different freshness values;
y porque el método comprende además: and because the method also includes:
c) la determinación de la frescura de la muestra del pescado objetivo a partir del valor interpolado en la etapa b3).  c) the determination of the freshness of the sample of the target fish from the value interpolated in step b3).
2. - Procedimiento según la reivindicación 1 , caracterizado porque comprende generar y almacenar en memoria al menos dicha curva de calibrado.  2. - Method according to claim 1, characterized in that it comprises generating and storing at least said calibration curve in memory.
3.- Procedimiento según una cualquiera de las reivindicaciones anteriores, caracterizado porque dicha etapa b) se realiza sobre la parte de la imagen adquirida correspondiente al iris del ojo del pescado.  3. Method according to any one of the preceding claims, characterized in that said step b) is performed on the part of the acquired image corresponding to the iris of the fish's eye.
4. - Procedimiento según la reivindicación 1 , 2 ó 3, caracterizado porque dicha imagen es una imagen digital obtenida mediante una cámara digital, y porque dichas condiciones determinadas incluyen utilizar una distancia entre el ojo del pescado y la lente de la cámara en un intervalo entre 10 y 30 cm y utilizar una fuente de iluminación de entre 2500 y 6500 grados Kelvin de temperatura de color.  4. - Method according to claim 1, 2 or 3, characterized in that said image is a digital image obtained by means of a digital camera, and that said determined conditions include using a distance between the fish's eye and the camera lens in an interval between 10 and 30 cm and use a lighting source between 2500 and 6500 degrees Kelvin of color temperature.
5. - Procedimiento según una cualquiera de las reivindicaciones anteriores, caracterizado porque dicho procesamiento de los datos crudos de la imagen de la etapa b1 ) incluye un pre-procesado o procesamiento inicial de los datos crudos de la imagen adquirida en la etapa a) para la corrección de deformaciones geométricas, eliminación de ruido, corrección del nivel de grises y corrección del enturbiado. 5. - Method according to any one of the preceding claims, characterized in that said processing of the raw data of the image of step b1) includes a preprocessing or initial processing of the raw data of the image acquired in stage a) for the correction of geometric deformations, noise elimination, gray level correction and cloud correction.
6.- Procedimiento según la reivindicación 5, caracterizado porque comprende: 6. Method according to claim 5, characterized in that it comprises:
- realizar dicha segmentación de la etapa b1 ) sobre la imagen pre-procesada en una pluralidad de áreas de interés para fijar los parámetros de color con respecto al iris del ojo de la muestra de pescado; - performing said segmentation of step b1) on the pre-processed image in a plurality of areas of interest to set the color parameters with respect to the iris of the eye of the fish sample;
- realizar una etapa de reconocimiento del ojo del pescado centrando la imagen sobre el mismo; y  - perform a stage of recognition of the eye of the fish centering the image on it; Y
- realizar la etapa b2) sobre dicha imagen centrada sobre el ojo del pescado.  - perform stage b2) on said image centered on the fish's eye.
7.- Procedimiento según una cualquiera de las reivindicaciones anteriores, caracterizado porque para verificar si se ha mantenido el pescado objetivo refrigerado a 0°C o por debajo de 0°C sin alcanzar su temperatura o punto de congelación, el procedimiento comprende comparar el valor de frescura determinado en la etapa c) con el valor de frescura que se muestra en una etiqueta de trazabilidad del pescado objetivo. 7. Method according to any one of the preceding claims, characterized in that to verify whether the target fish has been kept refrigerated at 0 ° C or below 0 ° C without reaching its temperature or freezing point, the method comprises comparing the value of freshness determined in step c) with the freshness value shown on a traceability label of the target fish.
8. - Procedimiento según una cualquiera de las reivindicaciones anteriores, caracterizado porque comprende:  8. - Method according to any one of the preceding claims, characterized in that it comprises:
i) realizar dicha etapa a) mediante un dispositivo de computación portátil con cámara digital y capacidad de comunicaciones;  i) perform said step a) by means of a portable computing device with digital camera and communications capability;
ii) enviar, dicho usuario, dicha imagen adquirida o información asociada a la misma, desde dicho dispositivo de computación portátil hasta un dispositivo de computación remoto con acceso a dicha curva de calibrado, que es al menos una;  ii) sending said user, said acquired image or associated information therefrom, from said portable computing device to a remote computing device with access to said calibration curve, which is at least one;
iii) realizar, por parte del dispositivo de computación remoto, al menos dichas etapas b3) y c); y  iii) perform, by the remote computing device, at least said steps b3) and c); Y
iv) enviar, desde el dispositivo de computación remoto hasta el dispositivo de computación portátil, el valor de frescura determinado en la etapa c).  iv) send, from the remote computing device to the portable computing device, the freshness value determined in step c).
9. - Procedimiento según la reivindicación 8, caracterizado porque dicha etapa ii) comprende enviar la imagen adquirida y porque dicha etapa iii) comprende realizar también, por parte del dispositivo de computación remoto, las etapas b1 ) y b2).  9. - Method according to claim 8, characterized in that said stage ii) comprises sending the acquired image and that said stage iii) also comprises carrying out, by the remote computing device, steps b1) and b2).
10.- Procedimiento según la reivindicación 8, caracterizado porque comprende realizar dichas etapas b1 ) y b2) por parte del dispositivo de computación portátil, y porque dicha etapa ii) comprende enviar dicha información asociada a la imagen adquirida, siendo dicha información el valor o valores determinados en la etapa b2).  10. Method according to claim 8, characterized in that it comprises performing said steps b1) and b2) by the portable computing device, and because said step ii) comprises sending said information associated with the acquired image, said information being the value or values determined in stage b2).
11.- Sistema para determinar la frescura del pescado basado en el procesamiento de imágenes oculares, configurado para implementar el procedimiento según una cualquiera de las reivindicaciones anteriores, que comprende: - medios de adquisición de imágenes para realizar la etapa a); y11. System for determining the freshness of the fish based on the processing of ocular images, configured to implement the method according to any one of the preceding claims, comprising: - means of acquiring images to perform stage a); Y
- un sistema electrónico, en conexión con dichos medios de adquisición de imágenes para recibir las imágenes adquiridas, y que está configurado para implementar la etapa b); y - an electronic system, in connection with said image acquisition means to receive the acquired images, and which is configured to implement step b); Y
estando dicho sistema caracterizado porque el sistema electrónico está configurado para implementar las etapas b1 ), b2), b3) y c) del procedimiento, comprendiendo o teniendo acceso a al menos una memoria donde se encuentra registrada al menos la curva de calibrado, que es al menos una, para realizar la etapa b3). said system being characterized in that the electronic system is configured to implement steps b1), b2), b3) and c) of the procedure, comprising or having access to at least one memory where at least the calibration curve is registered, which is at minus one, to perform stage b3).
12. - Sistema según la reivindicación 11 , caracterizado porque los medios de adquisición de imágenes comprenden:  12. - System according to claim 11, characterized in that the image acquisition means comprise:
- una cámara digital (C); y  - a digital camera (C); Y
- un dispositivo auxiliar separador (D) a disponer entre la lente (L) de la cámara digital (C) y el ojo del pescado cuya imagen se desea adquirir, que está formado por un cuerpo (B) de material no transparente de entre 10-30 cm de altura con un orificio longitudinal pasante (OI ) para comunicar lumínicamente a ambos, la lente (L) de la cámara (C) y el ojo del pescado, cuando se dispone entre ambos.  - an auxiliary separating device (D) to be arranged between the lens (L) of the digital camera (C) and the fish eye whose image is to be acquired, which is formed by a body (B) of non-transparent material of between 10 -30 cm high with a through hole (OI) to lightly communicate both the lens (L) of the camera (C) and the eye of the fish, when it is arranged between them.
13. - Sistema según la reivindicación 12, caracterizado porque dicho dispositivo auxiliar separador (D) comprende unos medios de iluminación dispuestos y configurados para iluminar a dicho ojo del pescado a través del orificio longitudinal pasante (OI ) de dicho cuerpo (B).  13. - System according to claim 12, characterized in that said auxiliary separating device (D) comprises lighting means arranged and configured to illuminate said fish eye through the through longitudinal hole (OI) of said body (B).
14. - Sistema según la reivindicación 13, caracterizado porque dichos medios de iluminación comprenden una fuente de luz (F) introducida, al menos parcialmente, en un orificio transversal pasante (02) realizado en una pared del cuerpo (B), para iluminar el interior del orificio longitudinal pasante (OI ).  14. - System according to claim 13, characterized in that said lighting means comprise a light source (F) introduced, at least partially, into a through transverse hole (02) made in a wall of the body (B), to illuminate the inside the longitudinal through hole (OI).
15.- Sistema según la reivindicación 14, caracterizado porque dicho orificio transversal pasante (02) tiene un diámetro de entre 2 y 5 cm y se encuentra ubicado a una altura de entre 2,5 y 7,5 cm desde la base del cuerpo (B) a disponer sobre el pescado.  15. System according to claim 14, characterized in that said through transverse hole (02) has a diameter of between 2 and 5 cm and is located at a height of between 2.5 and 7.5 cm from the base of the body ( B) to be arranged on the fish.
16.- Sistema según una cualquiera de las reivindicaciones 11 a 15, caracterizado porque está configurado para implementar el procedimiento de la reivindicación 8, para lo cual el sistema comprende:  16. System according to any one of claims 11 to 15, characterized in that it is configured to implement the method of claim 8, for which the system comprises:
- un dispositivo de computación portátil (M) con capacidad de comunicaciones, que incluye a una cámara digital (C) de dichos medios de adquisición de imágenes y a una parte local de dicho sistema electrónico para implementar dichas etapas i) y ii); y - un dispositivo de computación remoto (SR) con capacidad de comunicaciones, que incluye a una parte remota de dicho sistema electrónico para implementar las etapas iii) y iv). - a portable computing device (M) with communications capability, which includes a digital camera (C) of said image acquisition means and a local part of said electronic system to implement said stages i) and ii); Y - a remote computing device (SR) with communications capability, which includes a remote part of said electronic system to implement stages iii) and iv).
17. - Sistema según la reivindicación 16 cuando depende de la 12, caracterizado porque para implementar el procedimiento de la reivindicación 10, el sistema también comprende a dicho dispositivo auxiliar separador (D) a utilizar junto con el dispositivo de computación portátil (M) para implementar la etapa i).  17. - System according to claim 16 when it depends on 12, characterized in that to implement the method of claim 10, the system also comprises said auxiliary separator device (D) to be used together with the portable computing device (M) for implement stage i).
18. - Sistema según la reivindicación 17, caracterizado porque dicha capacidad de comunicaciones de ambos dispositivos de computación (M, SR) es de tipo inalámbrico.  18. - System according to claim 17, characterized in that said communication capacity of both computing devices (M, SR) is of the wireless type.
19. - Sistema según la reivindicación 17 ó 18, caracterizado porque el dispositivo de computación portátil (M) dispone de una pantalla (V) donde mostrar el valor de frescura recibido en la etapa iv).  19. - System according to claim 17 or 18, characterized in that the portable computing device (M) has a screen (V) showing the value of freshness received in step iv).
20. - Programa de ordenador adaptado para ejecutar el procedimiento según una cualquiera de las reivindicaciones 1 a 12, incluyendo la realización de las etapas b1 ), b2), b3) y c).  20. - Computer program adapted to execute the method according to any one of claims 1 to 12, including carrying out steps b1), b2), b3) and c).
PCT/ES2013/000220 2012-10-04 2013-10-04 Method and system for determining the freshness of fish, based on the processing of ocular images, and computer program implementing the method WO2014053679A1 (en)

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CN108535431A (en) * 2018-03-27 2018-09-14 海南翔泰渔业股份有限公司 A kind of whole fish of aquatic products is cut open the chest formula freshness detecting system
CN111724350A (en) * 2020-05-29 2020-09-29 北京农业信息技术研究中心 Nondestructive testing method and device for freshness of fish body
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