JP2004301690A - Method for detecting foreign object and impurities in food - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a detection method of foreign objects and impurities for precisely removing the foreign objects and impurities contained in food, such as fruits. <P>SOLUTION: In the detection method of foreign objects and impurities, first, the visible light of reflection light obtained by irradiating food containing fruit, or the like, and foreign objects and impurities contained in the food with light, and the absorption spectrum of near infrared rays are measured. Then, a second-order differential processing is applied to the absorption spectrum, and a wavelength band for indicating a different, second-order differential spectrum between the food and foreign object and/or impurities is selected. Then, a second-order differential spectral image of the selected wavelength band is created for the food, thus detecting the foreign objects and impurities contained in the food. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a method for detecting foreign substances and foreign substances mixed in foods using visible light and near-infrared light. INDUSTRIAL APPLICABILITY The present invention is particularly suitably used for foods that may contain foreign substances and / or contaminants including chlorophyll.
[0002]
[Prior art]
In the process of manufacturing processed foods, there is a risk that foreign substances such as hair, stones, threads, insects, stones, metal, glass, plastic, vinyl, and paper are mixed in many stages in the process. If the food is processed in a state in which such foreign matter is contained, the food is shipped with the foreign matter included in the processed food, which is a problem in food hygiene.
[0003]
In addition, when producing processed foods containing fruits such as fruit syrup pickles, jelly, jam, fruit yogurt, fruit ice cream, etc., fruit pulp such as blueberries, strawberry, plums, prunes, etc. is mixed and used . The fruit pulp, also called fruit preparation, is processed by removing contaminants such as leaves, stems, peduncles, branches, seeds, hulls, endothelium, pulp and sepals from the harvested fruits. . If the processing of fruit pulp is performed while such impurities are contained, such impurities will remain in the processed food manufactured using the same, and the quality of the food will be reduced. From the viewpoint of maintaining the quality of food.
[0004]
Therefore, such foreign substances and impurities must be removed during the food processing stage. As a removal method, a method has been employed in which an operator arranged in a food production line visually selects and removes foreign matter. However, in this method, a worker for removing foreign matter must be always arranged in the line, which requires high labor costs and is disadvantageous in cost. Further, in the manual removal of foreign matter, there is a high risk of overlooking the foreign matter, and it is not always possible to surely remove the foreign matter. Therefore, there is a problem in the accuracy of foreign matter removal.
[0005]
In order to solve this problem, Patent Documents 1 to 3 disclose apparatuses and methods for automatically removing foreign substances contained in food (or food raw materials). Further, Patent Literature 4 discloses a method of automatically identifying a defective product having insect eating, spots, cracks, decay, and the like from fruits (particularly, prunes).
[0006]
Patent Literature 5 describes a method for evaluating the taste of rice by detecting the absorbance of light in an absorption band characteristic of chlorophyll in the visible region, which is not intended for removing foreign substances. Have been.
[0007]
[Patent Document 1]
JP 2001-99783 A (released on April 13, 2001)
[0008]
[Patent Document 2]
Japanese Patent Application Laid-Open No. 2002-20501 (published on July 23, 2002)
[0009]
[Patent Document 3]
JP-A-2000-157936 (released on June 13, 2000)
[0010]
[Patent Document 4]
JP-T 2001-502804 (published on February 27, 2001)
[0011]
[Patent Document 5]
JP 2001-59815 A (released on March 6, 2001)
[0012]
[Problems to be solved by the invention]
All of the methods described in Patent Documents 1 to 4 detect a foreign substance by using a color difference between the foreign substance and the food, and therefore detect a foreign substance or a defective product similar in color to the food as a foreign substance. It is considered impossible to do so, and the accuracy of foreign matter removal is not always high.
[0013]
In addition, when the food contains fruits, at the stage of processing the food, impurities such as leaves, stems, stalks, branches, seeds, hulls, endothelium, pulp, and sepals are completely contained in the food. It is very likely that they have been mixed in without being removed. However, the methods (or devices) described in Patent Documents 1 to 4 cannot detect such contaminants contained in fruits.
[0014]
The present invention has been made in view of the above problems, and a foreign matter / contaminant detection method capable of removing foreign matter and contaminants contained in food with higher accuracy than conventional methods. The purpose is to provide.
[0015]
[Means for Solving the Problems]
As a result of intensive studies on the above problems, the inventors of the present application measured the absorption spectra of the food and the near-infrared light of each of the foreign substances and / or contaminants mixed therein, and performed the second derivative processing on the absorption spectrum. As a result, it was confirmed that each of the second derivative spectra exhibited significantly different spectral characteristics in a specific wavelength band. Then, they have found that by capturing a second-order differential spectral image in the specific wavelength band, it is possible to detect foreign substances and / or foreign substances in food, and have completed the present invention.
[0016]
That is, the method for detecting foreign matter and / or contaminants according to the present invention uses visible light and near-infrared light of reflected light obtained by irradiating light to a food and foreign matter and / or contaminants contained in the food. Is measured, and a second derivative process is performed on the absorption spectrum to select a wavelength band showing a different second derivative spectrum between the food and the foreign substance and / or contaminant. On the other hand, a foreign substance and / or a foreign substance contained in the food is detected by creating a second derivative spectral image in the wavelength band.
[0017]
In this method for detecting foreign matter and / or foreign matter, first, an absorption spectrum is measured in advance for a food and a foreign matter or foreign matter that may be contained in the food, and a second differentiation process is performed on the absorption spectrum. I do. Next, the second derivative spectrum of the food is compared with the second derivative spectrum of a foreign substance and / or a foreign substance, and a wavelength band showing a different second derivative spectrum is found. Then, for the above-mentioned food to be detected (that is, food in which foreign matter or foreign matter may be mixed), a second derivative spectral image in the wavelength band is created, and the foreign matter and / or Or to detect foreign substances.
[0018]
According to the above method, since the second derivative spectral image is created limited to the wavelength band showing the second derivative spectrum different between the food and the foreign matter and / or the foreign matter, the obtained second derivative spectral image is obtained. Thus, the food can be easily distinguished from foreign substances and / or contaminants. For this reason, foreign substances and / or foreign substances can be detected more accurately and reliably than the conventional method, and the risk of foreign substances and foreign substances being mixed in the food production process can be reduced.
[0019]
In order to create the spectral image, for example, it is possible to use an apparatus including a spectral unit that splits reflected light from an object and an image forming unit that creates an image using light of a specific wavelength. it can.
[0020]
In the method for detecting foreign matter and / or impurities according to the present invention, in addition to the above-described method, it is preferable that the second-order differential spectral image is further subjected to a binarization process.
[0021]
According to the above method, by binarizing the second-order differential spectral image, the components in the food can be clearly distinguished from other foreign substances and impurities, and more accurate foreign substances and And / or detection of contaminants.
[0022]
Further, in the method for detecting foreign matter and / or contaminants according to the present invention, it is preferable that the wavelength band exists in a range of 600 nm to 700 nm. In particular, it is preferable to apply the above-described method when there is a possibility that foreign substances and / or contaminants containing chlorophyll are mixed in the food to be detected.
[0023]
It is highly likely that various foods contain chlorophyll-containing leaves, stems, branches, sepals, and the like as impurities. This chlorophyll exhibits a unique second derivative spectrum at a wavelength within a range from 600 nm to 700 nm. According to the above method, since the second derivative spectroscopic image is created for the wavelength within the range of 600 nm or more and 700 nm or less, the above-mentioned impurities including chlorophyll can be detected with high accuracy. Therefore, it is possible to reduce the risk of contamination by contaminants at the stage of manufacturing various processed foods, and to improve the quality of foods.
[0024]
As described above, the method for detecting foreign matter and / or contaminants according to the present invention uses leaves, stems, stalks, branches, seeds, hulls, endothelium, and the like that are likely to be mixed into foods including fruits and vegetables. Impurities such as fruit cores and sepals can be detected with high accuracy. Therefore, in the method for detecting foreign matter and / or contaminants according to the present invention, the food preferably contains fruits and vegetables.
[0025]
In addition, as a detection apparatus for performing the foreign substance and / or foreign substance detection method of the present invention, the following apparatuses can be exemplified.
[0026]
That is, an irradiating means for irradiating the food with light, a spectral filter for spectrally separating light in a wavelength band showing a different second derivative spectrum between the food and a foreign substance and / or an impurity contained in the food, Imaging means for capturing a spectral image obtained by light in a wavelength band; and second-order differentiation processing of the spectral image taken by the image-capturing means to create a second-order differential spectral image. And a foreign matter and / or contaminant detection device provided with an image processing means for performing a conversion process.
[0027]
The above-described detection device previously confirms a wavelength band having a different second derivative spectrum between a component in a food and a foreign substance and / or a foreign substance mixed in the food, and An imaging unit captures a spectral image obtained by light. Subsequently, the image processing means performs a second differentiation process on the spectral image to create a second differential spectral image, and performs a binarization process on the second differential spectral image to be a food component, a foreign substance, and / or This is to determine whether the substance is a foreign substance.
[0028]
According to the above configuration, foreign substances and / or contaminants contained in food can be reliably detected, and the detection method of the present invention can be performed.
[0029]
Note that chlorophyll contained in leaves, branches, and the like, which are highly likely to be mixed into foods including fruits, exhibits a unique absorption spectrum with respect to light in a wavelength band in a range of 600 nm to 700 nm. Therefore, the above-mentioned detection device can select the wavelength band within the range of 600 nm or more and 700 nm or less so that when the food to be detected particularly contains fruits, it can reduce impurities such as leaves and branches mixed therein. It can be detected with high accuracy.
[0030]
Also, among the various fruits, particularly for blueberries, by creating a second derivative spectroscopic image at a wavelength of 675 nm, it is possible to reliably detect impurities such as leaves and branches in the food.
[0031]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, the present invention will be described more specifically, but the present invention is not limited to this description.
[0032]
The method for detecting foreign matter and / or foreign matter according to the present invention is for detecting foreign matter and foreign matter mixed in a food. Here, an example of the above-mentioned food, particularly one containing a fruit, will be described. Will be explained.
[0033]
The above-mentioned foods containing fruits are, specifically, blueberries and strawberry used as one of the raw materials when manufacturing processed foods containing fruits such as fruit syrup, jam, or jelly, yogurt, and ice cream. , Plum, prune, raspberry, cranberry, blackberry, cassis, orange, navel, grapefruit, sweetie, lemon, summer orange, peach, apple, pine, mango, banana, papaya, melon, aloe, cherry, grape, pear, pear, Fruit preparations containing one or more kinds of fruit pulp such as karin, persimmon, loquat, kiwi, apricot, litchi, raisin and the like. However, the foods to be subjected to the detection method of the present invention include not only the above-mentioned fruits but also any foods having a difference in the second derivative spectrum.
[0034]
There is a risk that hair, stones, threads, insects, or small pieces of metal glass, plastic, or the like may be mixed as foreign substances in each step of the production of foods. If the food is manufactured with such foreign matter mixed therein, it becomes a foreign matter mixed product, resulting in a deterioration in quality and a risk of secondary contamination by bacteria adhering to the foreign matter, which is not preferable in food hygiene.
[0035]
In addition, foods containing the fruit pulp as described above should be mixed into the food without removing impurities such as leaves, stems, stalks, branches, and seeds attached to the harvested fruits. Can often occur, but such contaminants impair the flavor and texture of the food, and thus are preferably removed.
[0036]
The method of the present invention for detecting foreign matter and / or contaminants (hereinafter referred to as foreign matter / contaminants) is intended to remove foreign matter / contaminants that are not desirably mixed into and left in food as described above. And measuring the absorption spectrum of visible light and near-infrared light of reflected light obtained by irradiating light to a food and a foreign substance and / or contaminant contained in the food. Performing a second derivative process on the absorption spectrum, selecting a wavelength band showing a different second derivative spectrum between the food and the foreign substance and / or contaminant, The method is characterized in that foreign substances and / or contaminants contained in the food are detected by creating a second derivative spectral image.
[0037]
FIG. 1 shows an example of a configuration of a foreign matter / contaminant detection device for implementing the foreign matter / contaminant detection method of the present invention. The above-mentioned detection device is a detection device for detecting foreign substances and foreign substances contained in foods whose main component is fruits, in particular, fruit 1 / juice 2 (food) to be detected, and a mixture thereof. Illumination 4 (irradiation means) for irradiating white light 5 (light) to foreign matter / contaminants 3 present, liquid crystal tunable filter 6 (spectral filter) for dispersing reflected light reflected from a detection target, A CCD camera 7 (imaging means) for photographing an image obtained by the light dispersed by the tunable filter 6, and an image processing such as a second differentiation process and a binarization process on the image obtained by the CCD camera 7. And an image processing means (not shown) for performing the processing. The liquid crystal tunable filter 6 is characterized in that it separates light in a wavelength band showing a second derivative spectral characteristic different between the fruit 1 / juice 2 and the foreign matter / contaminant 3. is there.
[0038]
If the detection device as shown in FIG. 1 is used, the method for detecting foreign matter / contaminants according to the present invention can be performed. Subsequently, each step of the method for removing foreign matter / contaminants of the present invention using the above detection device will be described in detail below.
[0039]
In the method for removing foreign matter and impurities, first, the absorption spectrum of visible light and near-infrared light of the reflected light obtained by irradiating the food and the foreign matter and impurities contained in the food with light, respectively. Measure. Here, the visible light and the near-infrared light refer to light having a wavelength of 340 to 2500 nm. In the step of measuring the absorption spectrum, a food to be detected and some foreign substances / contaminants that may be mixed in the food are picked up, and the absorption spectrum is measured for them.
[0040]
Subsequently, a second derivative process is performed on each of the measured absorption spectra, and a wavelength band showing a different second derivative spectrum between the food and the foreign substance and / or contaminant is selected.
[0041]
Here, an example in which the step of performing the above-described second derivative processing and the step of selecting a wavelength band are performed on a food containing blueberry as a main component will be described with reference to FIG. FIG. 3 shows the results for the blueberry (A) as a food, the leaves (B) and branches (C) as contaminants, and the stones (D), hair (E) and insects (F) as foreign substances. 10 is a graph showing a result obtained by performing a second-order differentiation process on the obtained absorption spectrum.
[0042]
As shown in FIG. 3, as a result of the absorption spectrum measurement, it can be seen that the leaves (B) and the branches (C) show a second-order differential spectrum characteristic different from that of the blueberries (A) in a wavelength band around 675 nm. Therefore, in the step of selecting a wavelength band, a wavelength band near 675 nm is selected as the above-mentioned wavelength band.
[0043]
When the wavelength band is selected in this manner, subsequently, a secondary differential spectral image is created for the food to be detected. The creation of the second derivative spectral image can be performed by the detection device shown in FIG.
[0044]
That is, in the detection device, the liquid crystal tunable filter 6 disperses the light in the above-mentioned wavelength band, the CCD camera 7 captures an image obtained by the light in the above-mentioned wavelength band, and the image processing means captures an image using the CCD camera 7. It is also possible to create a second-order differential spectral image by performing a second-order differential process on the obtained image, and to perform a binarization process on the second-order differential spectral image.
[0045]
As a result, even if there is no difference between the absorption spectra of the food and the foreign substance / contaminant, there may be a difference between the second derivative spectra. -It becomes possible to detect impurities. That is, more types of foreign substances and / or contaminants can be detected.
[0046]
For example, for the blueberry (A) shown in FIG. 3 and the leaves (B) and branches (C) contained therein, a second derivative spectral image around a wavelength of 675 nm is created and binarized, and as shown in FIG. As shown in (d), the leaves and branches contained in the food are clearly indicated in white, and the other food components are expressed in black. Therefore, it is necessary to accurately detect the contaminant leaves and branches. Can be.
[0047]
As described above, impurities contained in foods including fruits and vegetables such as leaves, branches and sepals contain chlorophyll. Chlorophyll exhibits a unique second derivative spectrum at a wavelength within the range of 600 nm to 700 nm.
[0048]
Therefore, it is preferable that the wavelength band exists in a range of 600 nm or more and 700 nm or less.
[0049]
Also, among various fruits, particularly in the case of foods mainly containing blueberries, it is preferable to select a wavelength band around 675 nm (that is, 660 nm to 690 nm) as the above-mentioned wavelength band.
[0050]
According to this, as shown in the examples described later, it is possible to clearly detect leaves, branches, and the like mixed in the food as impurities.
[0051]
Further, in the method for detecting foreign matter / contaminants of the present invention, in order to detect more kinds of foreign matter / contaminants, in the above-described detection method, when the absorption spectrum is measured, the food and the foreign matter are detected. And / or another wavelength band showing an absorption spectrum different from that of impurities may be selected, and a spectral image of the another wavelength band may be further created for the food.
[0052]
That is, in the method for detecting foreign matter / contaminants of the present invention, after the step of measuring the absorption spectrum, a comparison is made for each absorption spectrum of food and foreign matter / impurities, and between the food and the foreign matter / impurities. The method may further include a step of selecting another wavelength band showing a different absorption spectrum, and may further create a spectral image of the other wavelength band in the step of creating the second-order differential spectral image.
[0053]
Here, an example in which the above-described step of measuring the absorption spectrum and the step of selecting the other wavelength band are performed on a food containing blueberry as a main component will be described with reference to FIG. FIG. 2 shows the absorption of blueberries (A) as food, leaves (B) and branches (C) as impurities, and stones (D), hair (E) and insects (F) as foreign substances. It is a graph of the result of having measured the spectrum.
[0054]
As shown in FIG. 2, as a result of the absorption spectrum measurement, for the stone (D) and the hair (E), blueberries (wavelengths hatched in FIG. 2) in the wavelength band of 440 nm or more and 460 nm or less (FIG. 2). It can be seen that it exhibits an absorption spectrum characteristic different from that of A). Therefore, in the step of selecting another wavelength band, a wavelength band of 440 nm to 460 nm is selected as the another wavelength band (second wavelength band).
[0055]
Subsequently, in the above-described detection method, a spectral image of another selected wavelength band is created. In creating this spectral image, the detection device shown in FIG. 1 can be used.
[0056]
FIGS. 4E and 4F show an example of the spectral image created in the spectral image creating step. In this figure, the wavelength band of 440 nm or more and 460 nm or less is selected as the second wavelength band using the detection device shown in FIG. 1 in the blueberry containing the foreign substance and the contaminant for which the absorption spectrum shown in FIG. 2 was measured. FIG. 3 is a diagram illustrating a case where the spectral image is created, and a binarization process is performed on the spectral image.
[0057]
By performing binarization processing on the spectral image, as shown in FIGS. 4E and 4F, the stones contained in the food are expressed in white, and the other food components are expressed in black. Therefore, it is possible to detect a stone as a foreign matter with high accuracy.
[0058]
As shown in the graph of FIG. 2, when the absorption spectrum is measured for foods and foreign substances / contaminants, foreign substances such as hair and stones and foods such as fruits within a wavelength range of 400 nm or more and 500 nm or less. Show different absorbances. Therefore, in the foreign matter / contaminant detection method of the present invention, it is preferable that the another wavelength band exists in a range from 400 nm to 500 nm. Thus, it is considered that foreign substances such as stones and hair mixed in food can be detected.
[0059]
As described above, the method for detecting foreign matter and / or contaminants of the present invention further includes a step of creating a spectral image for another wavelength band showing a different absorption spectrum, so that more foreign matter and / or contaminants are contained. It is believed that the object can be further detected.
[0060]
In the foreign matter / contaminant detection method of the present invention, it is preferable to further binarize the spectral image or the second derivative spectral image obtained as described above.
[0061]
According to this, it is possible to clearly distinguish the components in the food from the other foreign substances and impurities as black and white two-color images.
[0062]
Further, in the present invention, the foreign substance is a substance other than food ingredients mixed in the process of manufacturing food, and specifically, hair, stone, thread, insect, metal, glass, plastic, vinyl, paper, wood chips. , Rubber and the like. In addition, the above-mentioned contaminants refer to those which are contained in the raw materials of food but should be removed when the product is completed. As the impurities, more specifically, leaves, stems, stems, branches, seeds, hulls, endothelium, fruit cores, sepals, carcinomas, cartilage, which are attached to fruits and vegetables at the time of harvesting, Examples include immature fruits.
[0063]
In the present embodiment, the method and apparatus for detecting foreign substances / contaminants contained in food containing fruit as a main component have been described. However, the present invention is not limited to this. It can also be used to detect foreign substances. In this case, a second derivative spectral image in a wavelength band showing different characteristics between the second derivative spectrum of the component in each food and the second derivative spectrum of a foreign substance or an impurity may be created.
[0064]
【Example】
Hereinafter, examples of the present invention will be described, but the present invention is not limited to the description.
[0065]
In the present embodiment, a fruit preparation containing blueberry pulp as a main component is used as a food, and a mixture of blueberry leaves, blueberry branches, stones, hair, and insects as foreign matter and impurities in the fruit preparation is used. Food samples. In this example, the apparatus shown in FIG. 1 was used as the foreign matter and / or foreign matter detection device of the present invention.
[0066]
(1) Measurement of absorption spectrum
In this example, first, an absorption spectrum obtained by irradiating the food sample with light was measured. The absorption spectrum is measured by irradiating the food sample (fruit 1 / juice 2) with white light 5 from the illumination 4 using the detection device shown in FIG. Was performed by measuring
[0067]
The result is shown in FIG. In FIG. 2, the horizontal axis indicates wavelength (nm), and the vertical axis indicates absorbance. In the graph of FIG. 2, the thick line of A indicates fruits, the thin broken line of B indicates leaves, the dashed line of C indicates a branch, the thick broken line of D indicates a stone, the two-dot chain line of E indicates hair, and F The thin lines indicate insects.
[0068]
As shown in FIG. 2, at wavelengths in the range of 440 nm to 460 nm, which are shaded in the graph, blueberry (A) and stone (D) show clearly different absorbances, and blueberry (A) and hair ( E) also showed a slightly different absorbance. From these results, it is considered that there is a high possibility that blueberry (A) and stone (D) show different absorption spectra at wavelengths in the range of 440 nm to 460 nm. At the same wavelength in the range of 440 nm to 460 nm, it is possible that blueberry (A) and hair (E) also show different absorption spectra.
[0069]
(2) Second derivative processing of absorption spectrum
Subsequently, a secondary differentiation process was performed on each of the absorption spectra obtained in the above (1). The result is shown in FIG. In FIG. 3, the horizontal axis indicates the wavelength (nm), and the vertical axis indicates the absorbance. In the graph of FIG. 3, the thick line of A represents fruit, the thin broken line of B represents leaves, the dashed line of C represents a branch, the thick broken line of D represents a stone, the two-dot chain line of E represents hair, and F represents the hair. The thin lines indicate insects.
[0070]
As shown in FIG. 3, it was confirmed that the fruit (A) and the leaves (B) / branches (C) exhibited significantly different spectra at a wavelength around 675 nm.
[0071]
(3) Image shooting and binarization processing
Next, an image of the food sample was taken using the detection device shown in FIG. The results are shown in FIGS.
[0072]
FIGS. 4A and 4B are images obtained when the food sample is photographed by the CCD camera 7 without spectral analysis. FIGS. 4C and 4D show that the CCD camera 7 captures a spectral image of wavelengths before and after 675 nm, and a second-order differential spectral image is created by image processing means (not shown). This is an image obtained when binarizing a spectral image. FIGS. 4E and 4F are images obtained when a CCD camera 7 captures a spectral image having a wavelength of about 450 nm and performs binarization processing by image processing means (not shown). .
[0073]
In each figure of FIG. 4, (a), (c), and (e) are images of the same food sample, and (b), (d), and (f) are images of the same food sample. It is.
[0074]
In FIGS. 4C and 4D, black portions are fruits and fruit juices, and white portions are leaves and branches. In FIGS. 4E and 4F, black portions are fruits and juice, and white portions are stones.
[0075]
As described above, by performing appropriate image processing on each of the spectral images around 675 nm or around 450 nm, leaves, branches and stones mixed in the food sample could be clearly detected.
[0076]
【The invention's effect】
As described above, according to the method for detecting foreign matter and / or contaminants of the present invention, visible light and near-reflection light obtained by irradiating a food and foreign matter and / or contaminants contained in the food with light are obtained. Measure the absorption spectrum of infrared light, perform a second derivative process on the absorption spectrum, and select a wavelength band showing a different second derivative spectrum between the food and the foreign substance and / or contaminant, The method is characterized in that foreign substances and / or contaminants contained in the food are detected by creating a second derivative spectral image in the wavelength band for the food.
[0077]
According to the above method, since the second derivative spectral image is created limited to the wavelength band showing the second derivative spectrum different between the food and the foreign matter and / or the foreign matter, the obtained second derivative spectral image is obtained. Thus, the food can be easily distinguished from foreign substances and / or contaminants. For this reason, the detection of foreign substances and / or contaminants can be performed more accurately and more reliably than the conventional method, and the effect of reducing the risk of contamination of foreign substances and contaminants in the food production process can be achieved.
[0078]
In the method for detecting foreign matter and / or impurities according to the present invention, in addition to the above-described method, it is preferable that the second-order differential spectral image is further subjected to a binarization process.
[0079]
According to the above method, by binarizing the secondary differential image, the components in the food can be clearly distinguished from other foreign substances and impurities, and more accurate foreign substances and / or Alternatively, there is an effect that foreign substances can be detected.
[0080]
The method for detecting a foreign substance and / or a foreign substance according to the present invention includes, in addition to the above-described method, a case in which a foreign substance and / or a foreign substance containing chlorophyll may be mixed in the food to be detected. Preferably, the wavelength band exists in a range of 600 nm or more and 700 nm or less.
[0081]
In particular, chlorophyll contained in leaves and branches that are highly likely to be mixed into foods including fruits and vegetables shows a unique second-order differential spectrum for light in a wavelength band in a range of 600 nm to 700 nm. . Therefore, according to the above-mentioned method, when there is a possibility that a foreign substance and / or a foreign substance containing chlorophyll is mixed in the food to be detected, the foreign substance such as a leaf or a branch is mixed. Can be detected with high accuracy.
[Brief description of the drawings]
FIG. 1 is a schematic diagram showing a configuration of an example of a foreign matter and / or foreign matter detection device of the present invention.
FIG. 2 is a graph showing the results of measuring absorption spectra obtained when light was applied to fruits (blueberries) and foreign substances / contaminants in this example.
FIG. 3 is a graph showing the result of second-order differentiation of an absorption spectrum obtained when a fruit (blueberry) and a foreign substance / impurity are irradiated with light in this example.
FIGS. 4A to 4F show images obtained by irradiating a food sample containing fruits (blueberries) and foreign substances / contaminants with light in this example. (A) and (b) are images without spectrum, and (c) and (d) are images obtained by binarizing a second derivative spectral image in a wavelength band around 675 nm. (e) and (f) are images obtained by binarizing a spectral image in a wavelength band around 450 nm.
[Explanation of symbols]
1 fruit (food, fruit)
2 fruit juice (food / fruit)
3 Foreign matter / contaminants
4 Lighting (irradiation means)
5 White light (light)
6 Liquid crystal tunable filter (spectral filter)
7 CCD camera (imaging means)

Claims (3)

A visible light and a near-infrared light absorption spectrum of reflected light obtained by irradiating a food and a foreign substance and / or a foreign substance contained in the food with light are measured, and a second derivative of the absorption spectrum is measured. Performing a process, selecting a wavelength band showing a different second derivative spectrum between the food and the foreign substance and / or contaminant,
A method for detecting a foreign substance and / or a foreign substance, comprising detecting a foreign substance and / or a foreign substance contained in the food by creating a second derivative spectroscopic image of the wavelength band with respect to the food. The method for detecting foreign matter and / or contaminants according to claim 1, wherein the second derivative spectral image is further subjected to binarization processing. When there is a possibility that foreign substances and / or contaminants containing chlorophyll are mixed in the food to be detected, the wavelength band exists in a range of 600 nm or more and 700 nm or less. The method for detecting foreign matter and / or contaminants according to claim 1 or 2.

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