CN116342592B - Bufo siccus gland slurry drying monitoring method for processing toad venom - Google Patents

Bufo siccus gland slurry drying monitoring method for processing toad venom Download PDF

Info

Publication number
CN116342592B
CN116342592B CN202310595724.4A CN202310595724A CN116342592B CN 116342592 B CN116342592 B CN 116342592B CN 202310595724 A CN202310595724 A CN 202310595724A CN 116342592 B CN116342592 B CN 116342592B
Authority
CN
China
Prior art keywords
drying
image
toad venom
toad
venom
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202310595724.4A
Other languages
Chinese (zh)
Other versions
CN116342592A (en
Inventor
许晓玲
郭栋
马萌
王衍强
陈宁
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shandong Muze Traditional Chinese Medicine Decoction Pieces Co ltd
Original Assignee
Shandong Muze Traditional Chinese Medicine Decoction Pieces Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shandong Muze Traditional Chinese Medicine Decoction Pieces Co ltd filed Critical Shandong Muze Traditional Chinese Medicine Decoction Pieces Co ltd
Priority to CN202310595724.4A priority Critical patent/CN116342592B/en
Publication of CN116342592A publication Critical patent/CN116342592A/en
Application granted granted Critical
Publication of CN116342592B publication Critical patent/CN116342592B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformations in the plane of the image
    • G06T3/04Context-preserving transformations, e.g. by using an importance map
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/70Determining position or orientation of objects or cameras
    • G06T7/73Determining position or orientation of objects or cameras using feature-based methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/90Determination of colour characteristics
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30168Image quality inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30232Surveillance
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Quality & Reliability (AREA)
  • Image Processing (AREA)

Abstract

The invention relates to the technical field of image analysis, in particular to a toad gland slurry drying monitoring method for processing of venenum bufonis. Dividing a gray level image of a toad venom region into a plurality of detection regions, and obtaining gray level fluctuation indexes according to the color shade change degree and gray level overall trend of different position regions in the detection regions to further obtain drying characteristic indexes of the detection regions; obtaining a drying variation characteristic index according to the difference degree of the acquired historical toad venom region gray level image and the toad venom region image drying characteristic index, and determining a preliminary dried toad venom image; and obtaining a drying difference degree through the difference between the preliminary drying toad venom image and the standard image, obtaining a drying completion degree by combining the drying change characteristic index, and judging the drying condition of the corresponding toad venom through the drying completion degree. According to the invention, through image processing, the surface characteristics of the toad venom are analyzed more comprehensively and accurately, so that a more accurate drying state is obtained, and the quality of a toad venom product is ensured.

Description

Bufo siccus gland slurry drying monitoring method for processing toad venom
Technical Field
The invention relates to the technical field of image analysis, in particular to a toad gland slurry drying monitoring method for processing of venenum bufonis.
Background
Bufonis venenum is a Chinese medicinal preparation prepared by processing and drying white slurry secreted by otogland and skin gland of Bufo siccus animal. The surface of the dried toad venom slice is bright, and generally presents brown luster, which is obviously different from the surface of the non-dried toad serum. Because the gland serum itself contains a certain toxin, the toxin content in the toad gland serum is weakened by hot air drying, but the utilization value of the effective medical components in the toad venom is destroyed due to the influence of factors such as drying temperature or time, so that the surface drying state of the toad venom in the toad gland serum drying process needs to be monitored in time.
The existing method for guaranteeing the quality of the toad venom is mainly to carry out quality detection after drying toad venom of toad glands, but the cost consumption of the quality detection of all the toad venom is large, and the part of the effective components of the toad venom which are lost cannot be recovered, so that monitoring judgment is needed to be added in the drying process, and for the monitoring analysis of the surface of a toad venom image, the detail change of the surface of the toad venom is difficult to characterize only through gray level characteristics, so that the accuracy of the obtained drying state through the surface characteristic analysis is poor, and the quality of the obtained toad venom product is poor.
Disclosure of Invention
In order to solve the technical problems that detail change on the surface of the toad venom cannot be accurately represented in the prior art, the accuracy of analysis of a drying state is poor, and the quality of a obtained toad venom product is poor, the invention aims to provide a toad gland slurry drying monitoring method for toad venom processing, and the adopted technical scheme is as follows:
the invention provides a toad gland serous fluid drying monitoring method for processing toad venom, which comprises the following steps:
acquiring a toad venom region gray level image and a standard image at the current moment; constructing a detection area with a preset size by taking each pixel point in the toad venom area gray level image as a center, and dividing each detection area into a position area with the preset area size;
obtaining a gray scale fluctuation coefficient of each position area according to the gray scale variation degree of the pixel point in each position area, and obtaining a gray scale fluctuation index of each position area according to the integral trend of the gray scale value in each position area and the corresponding gray scale fluctuation coefficient; obtaining a drying characteristic index of the detection area according to all the gray level fluctuation indexes;
acquiring gray level images of all the historical toad venom areas before the current moment, and acquiring a drying variation characteristic index of the toad venom area gray level image according to the variation difference degree of the drying characteristic index for all the historical toad venom area gray level images and the toad venom area gray level image; determining a preliminary dried toad venom image according to the drying variation characteristic index;
for the standard image and the preliminary drying toad venom image, obtaining the drying difference degree of the preliminary drying toad venom image according to the difference degree of the drying characteristic indexes corresponding to the detection area; obtaining a drying completion degree according to the drying difference degree and the drying variation characteristic index of the preliminary drying toad venom image; and monitoring and judging the drying state of the toad venom corresponding to the preliminary dried toad venom image according to the drying completion degree.
Further, the method for acquiring the gray scale fluctuation coefficient comprises the following steps:
obtaining the gray value average value of each pixel point in all the position areas in a preset neighborhood range as the fluctuation value of each pixel point; in each position area, calculating the average value of fluctuation values of all pixel points, and taking the absolute value of the difference value between the fluctuation value of each pixel point and the average value of the fluctuation values as a fluctuation difference value;
and carrying out negative correlation mapping and normalization processing on the accumulated values of all fluctuation difference values in each position area to obtain the gray scale fluctuation coefficient of each position area.
Further, the method for acquiring the gray scale fluctuation index comprises the following steps:
calculating the average value of the gray values of all pixel points in each position area, and taking the average value of the gray values of the inverse proportion as a gray characteristic value; multiplying the gray characteristic value of each position area with a corresponding gray fluctuation coefficient to obtain a gray fluctuation index of each position area; the gray level fluctuation index and the drying characteristic index are in positive correlation.
Further, the method for acquiring the characteristic index of the drying variation comprises the following steps:
obtaining maximum and minimum values of the drying characteristic indexes in the gray level images of each historical toad venom region, and taking the maximum and minimum values corresponding to the gray level images of each historical toad venom region as a binary group;
calculating the binary norms between the binary group of each historical toad venom region gray level image and the binary group of the toad venom region gray level image to obtain a characteristic change value; and carrying out normalization treatment on the average value of all the characteristic variation values to obtain the drying variation characteristic index of the toad venom region gray level image.
Further, the method for acquiring the drying difference degree comprises the following steps:
acquiring a standard detection area of a standard image; calculating the absolute value of the difference value of the drying characteristic index between the standard detection area and the detection area at the same position in the standard image and the preliminary drying toad venom image to obtain a characteristic difference value;
and taking the accumulated value of all the characteristic difference values as the drying difference degree of the preliminary drying toad venom image.
Further, the method for obtaining the drying completion degree comprises the following steps:
multiplying the stoving difference degree of the preliminary stoving toad venom image and the stoving change characteristic index, and carrying out negative correlation mapping and normalization treatment on the product to obtain the stoving completion degree.
Further, the monitoring and judging of the drying state of the toad venom corresponding to the preliminary dried toad venom image according to the drying completion degree includes:
acquiring historical toad venom region gray level images corresponding to two times before the current time corresponding to the preliminary drying toad venom image, taking the historical toad venom region gray level images as gray level images to be analyzed, and calculating the average value of the corresponding three drying completion degrees in the preliminary drying toad venom image and the gray level images to be analyzed to serve as a state stability value; taking the difference value between the drying completion degree of the preliminary dried toad venom image and the state stability value as a drying state value;
and when the drying state value is smaller than a preset drying threshold value, marking the drying state of the toad venom corresponding to the preliminary drying toad venom image as a drying completion state.
Further, the method for acquiring the preliminary drying toad venom image comprises the following steps:
and when the characteristic index of the drying variation is smaller than or equal to a preset variation threshold, taking the corresponding gray level image of the toad venom area as a preliminary drying toad venom image.
The invention has the following beneficial effects:
according to the invention, the gray level image of the toad venom region is constructed into a plurality of detection regions, the position regions with the size of the preset region are divided for each detection region, the detail change of the color shade of the toad venom surface in different position regions is considered, the gray level fluctuation index is obtained according to the color shade change degree and the overall gray level value trend of each position region, the drying characteristic index is obtained by all gray level fluctuation indexes, and the local surface characteristics of the toad venom are more comprehensively represented by two aspects of color and gray level value. Further acquiring a historical toad venom region gray level image, acquiring a stable condition that a drying variation characteristic index reflects the surface characteristic of the toad venom region image according to the difference degree of the drying characteristic index of the historical toad venom region gray level image and the current toad venom region image, determining a preliminary drying toad venom image which is closer to finishing drying, and further accurately analyzing the drying state to acquire a more accurate drying result. The method comprises the steps of obtaining a drying difference degree through the difference of drying characteristic indexes between a preliminary drying toad venom image and a standard image, obtaining the drying completion degree of the preliminary drying toad venom image by combining the drying change characteristic indexes, analyzing the surface characteristic state of the toad venom in a finer manner, judging the drying condition of the corresponding toad venom according to the drying completion degree, and carrying out finer detailed change analysis on the surface characteristic of the toad venom to enable the monitoring of the drying state to be more comprehensive and accurate, so that the quality of a toad venom product is ensured.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for monitoring the drying of bufonid gland slurry for processing venenum according to one embodiment of the present invention.
Detailed Description
In order to further illustrate the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of a specific implementation, structure, characteristics and effects of a toad gland slurry drying monitoring method for processing venenum bufonis according to the invention, which is provided by the invention, with reference to the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the toad gland slurry drying monitoring method for processing the toad venom.
Referring to fig. 1, a flowchart of a toad gland slurry drying monitoring method for processing venenum bufonis according to an embodiment of the invention is shown, the method comprises the following steps:
s1: acquiring a toad venom region gray level image and a standard image at the current moment; and constructing a detection area with a preset size by taking each pixel point in the gray level image of the toad venom area as a center, and dividing each detection area into a position area with the preset area size.
The freshly collected toad gland serum has the characteristics of white serum, yellowish serum particles, light oil surface, high viscosity and the like, and in order to conveniently store and preserve the toad venom serum, the collected serum is required to be dried and processed to prepare thin round toad venom slices, and the toad venom is a traditional Chinese medicine product and is usually used for treating symptoms such as carbuncles, furuncles, abdominal pain, vomiting and diarrhea and the like. However, the toad venom is a kind of venom-containing slurry, which usually needs to be dried by hot air to weaken the toxin content in the toad venom, but also easily causes overdry condition, so that the effective medical components contained in the toad venom are destroyed when the toad venom is formed, and the quality of the toad venom is reduced, therefore, the drying monitoring is needed in the drying process, so as to improve the processing quality of the toad venom.
According to the invention, the surface detail change of the toad venom in the drying process is analyzed to realize the detection of the drying state, so that the surface of the toad venom subjected to the drying processing is shot and collected through the image collecting equipment. Taking the noise influence in the image into consideration, firstly preprocessing the toad venom surface image in three RGB channels by using a Gaussian filtering method, and converting the toad venom surface image into a gray image by adopting a weighted gray method to obtain the toad venom surface gray image. It should be noted that, the method of acquiring by a CCD camera, gaussian filtering of an image, and weighted graying of an image are all technical means well known to those skilled in the art, and will not be described herein.
In order to dynamically detect the drying state of the toad venom in real time, in the embodiment of the invention, the gray level image of the toad venom area is collected once every same time interval, the time interval is set to be 0.5 seconds, and an operator can adjust according to specific implementation conditions.
In order to avoid the influence of meaningless background pixel points on the accuracy of the subsequent drying state analysis, a region only containing the toad venom is extracted, in the embodiment of the invention, a maximum inter-class variance method is adopted to obtain a surface binary image, the background pixel points are set to 0, the toad venom region pixel points are set to 1, the surface binary image is used as a toad venom mask characteristic image, and the toad venom region gray image only containing the toad venom region is obtained by multiplying the toad venom surface gray image and the toad venom mask characteristic image. It should be noted that, since the position of the venenum bufonis does not significantly move during the processing process of the venenum bufonis, repeated calculation of mask feature images of the venenum bufonis at different moments is not needed, and the maximum inter-class variance method and the application of the mask images are all technical means well known to those skilled in the art, and are not described herein.
In order to improve the accuracy of the drying state, the invention needs to acquire a standard toad venom image in a drying completion state for comparison analysis, and in the embodiment of the invention, the acquisition of the standard image acquires the image of the surface of the toad venom according to the standard condition under 60-degree drying provided in traditional Chinese medicine decoction piece processing Specification of Shandong province, and the image containing the toad venom area after standard drying is acquired as the standard image.
The invention constructs a detection area with preset size by taking each pixel point in the toad venom area gray level image as the center, analyzes the surface detail change of the local area corresponding to each pixel point through the detection area, and in the embodiment of the invention, the detection area with preset size is an area range with 5 multiplied by 5 size by taking the pixel point as the center, the specific numerical value can be adjusted according to the specific implementation condition, and the surface detail characteristic analysis can be carried out in the detection area.
Because the thickness distribution of the whole surface structure of the toad slurry is uneven, and the variation characteristics of the thicker region and the thinner region are different, each detection region is also divided in the invention to obtain different position region analysis, so that the characteristic acquisition of the detection region is more accurate. Therefore, each detection area is divided into position areas with preset area size, in the embodiment of the present invention, the division of one position area is divided into a range with preset area size of 3×3 with pixel point as the center, the range is recorded as one position area, the rest areas in the detection area are recorded as another position area, the local feature is more carefully represented through two different position areas, and the specific division rule implementer can adjust according to specific situations, so that the present invention is not limited.
Thus, the acquisition of the toad venom region image and the division of the local detection region are completed, so that the subsequent analysis of the surface characteristics is facilitated.
S2: obtaining a gray scale fluctuation coefficient of each position area according to the gray scale variation degree of the pixel point in each position area, and obtaining a gray scale fluctuation index of each position area according to the integral trend of the gray scale value in each position area and the corresponding gray scale fluctuation coefficient; obtaining a drying characteristic index of the detection area according to all gray level fluctuation indexes; the gray scale fluctuation index and the drying characteristic index are in positive correlation.
The toad gland's toad serum is white when not stoving, and the toad venom after accomplishing the stoving is reddish brown according to experience, according to the toad surface moisture stoving in-process, its colour can be continuously darkened, corresponding grey value can be continuously reduced, when the toad venom is in the undried state, the grey value of pixel is the biggest, and the colour difference is less, all be in white state, along with the continuous stoving of toad surface, the colour is continuously darkened, the grey value in the image can be continuously diminish, the colour depth difference can increase because of the inhomogeneous change of stoving, and at near the completion of stoving, the colour difference can be diminish because the reddish brown of toad surface is not the reddish brown of complete homogeneity, consequently the colour depth difference is still great, namely reflect the stoving state of toad surface through to the colour depth difference and the grey value change two aspects of toad surface.
Firstly, analyzing the color shade difference in a detection area, obtaining a gray scale fluctuation coefficient by the gray scale variation degree of a pixel point in each position area, and reflecting the color shade difference degree in each position area by the gray scale fluctuation coefficient, wherein the gray scale fluctuation coefficient obtaining method specifically comprises the following steps:
the average value of gray values of each pixel point in all the position areas in a preset neighborhood range is obtained to be used as the fluctuation value of each pixel point, in one embodiment of the invention, the local color shade condition of each pixel point is reflected through first-order color moment, namely the color average value in a calculation range, and the image in the invention is a gray image, so that the first-order color moment is the gray value average value, and the preset neighborhood range is a neighborhood range with the size of 5 multiplied by 5 with each pixel point as the center, and the first-order color moment corresponding to the preset neighborhood range is used as the fluctuation value of the corresponding pixel point. It should be noted that the first-order color moment is a well-known technique known to those skilled in the art, and will not be described herein.
Further, in each position area, calculating the average value of fluctuation values of all pixel points, taking the absolute value of the difference value between the fluctuation value of each pixel point and the average value of the fluctuation values as a fluctuation difference value, reflecting the local color difference degree of each pixel point through the fluctuation difference value, and indicating that the larger the fluctuation difference value is, the larger the local color difference is, and the more likely the corresponding state is in an undried state. And carrying out negative correlation mapping and normalization processing on the accumulated values of all fluctuation difference values in each position area to obtain the gray scale fluctuation coefficient of each position area. Analyzing all pixel points, reflecting the overall color fluctuation condition of a position area, and providing the influence weight of color difference for the subsequent calculation of the drying characteristic through the gray scale fluctuation coefficient, wherein in the embodiment of the invention, the specific expression of the gray scale fluctuation coefficient is as follows:
in the method, in the process of the invention,represented as location areasIs used for the gradation fluctuation coefficient of (1),represented as location areasThe total number of the middle pixel points,represented as location areasThe mean value of the corresponding fluctuation values,represented as the first in the location areaThe fluctuation value of each pixel point,expressed as a natural constant.
Wherein, the liquid crystal display device comprises a liquid crystal display device,represented as the first in the location areaThe fluctuation difference value of each pixel point,the accumulated value of fluctuation difference values is mapped and normalized by an exponential function based on a natural constant, and the larger the fluctuation difference value is, the more likely the fluctuation difference value is in a drying state, so that the fluctuation difference value and the gray scale fluctuation coefficient have a negative correlation, and the smaller the gray scale fluctuation coefficient is, the more likely the fluctuation difference value is in an unwoven state.
After the analysis of the color difference in the detection area is completed, the gray value condition in the detection area is further analyzed, the overall gray trend in the position area is reflected through the average value of all gray values in each position area, the gray average value in inverse proportion is used as a gray characteristic value, the change influence of the gray value in the position area is reflected through the gray characteristic value, when the overall gray value of the position area is larger, the fact that the toad venom is more likely to be in an unwoven state at the moment is indicated, and the gray characteristic value is smaller.
The gray scale characteristic value and the gray scale fluctuation coefficient of each position area are combined for integral analysis, the gray scale fluctuation index corresponding to the position area can be obtained, the gray scale fluctuation index is reflected to the surface characteristic condition of each position area, the gray scale characteristic value and the gray scale fluctuation coefficient are multiplied to obtain the gray scale fluctuation index of each position area, when the gray scale characteristic value is smaller, the color fluctuation index is smaller, the corresponding area is more likely to be in an unwoven state, and the gray scale fluctuation index is smaller. The drying characteristic index can be obtained through the gray level fluctuation index, the gray level fluctuation index and the drying characteristic index are in positive correlation, in the embodiment of the invention, all gray level fluctuation indexes are comprehensively analyzed in an addition mode to obtain the drying characteristic index corresponding to the detection area, and the expression of the specific drying characteristic index is as follows:
in the method, in the process of the invention,represented as detection areaIs characterized in that the drying characteristic index of the furnace is that,represented as location areasIs used for the gradation fluctuation coefficient of (1),represented as location areasIs used for the gray scale characteristic value of (a),represented as detection areaTotal number of middle location areas.
Wherein, the liquid crystal display device comprises a liquid crystal display device,represented as location areasWhen all the gray scale fluctuation indexes in the detection area are larger, the corresponding detection area is more likely to be in a drying state, so that the gray scale fluctuation indexes and the drying characteristic indexes have positive correlation, and in other embodiments of the invention, other basic mathematical operations can be selected to reflect that the gray scale fluctuation indexes and the drying characteristic indexes have positive correlation, such as multiplication and the like, without limitation.
Thus, the surface characteristic change analysis of each detection area is completed, and the surface characteristic of each detection area is characterized by two aspects of color difference and gray level change so as to facilitate the subsequent analysis of the drying state.
S3: acquiring gray level images of all the historical toad venom areas before the current moment, and acquiring a drying variation characteristic index of the toad venom area gray level image according to the variation difference degree of the drying characteristic index for all the historical toad venom area gray level images and the toad venom area gray level images; and determining a preliminary dried toad venom image according to the drying variation characteristic index.
After the analysis of the surface characteristics of the corresponding part of each pixel point in the gray level image of the toad venom region is completed, the change degree of the surface characteristics can be analyzed according to the historical image shot before the current moment, and when the toad venom is closer to the drying completion state, the characteristics of the surface of the toad venom are closer to the stable state, so that all the gray level images of the historical toad venom region before the current moment are acquired, and the acquisition of the drying characteristic index can be carried out on each gray level image of the historical toad venom region. It should be noted that, because the drying process is a continuous process, the corresponding venenum bufonis cannot finish drying when the drying process is just started, so that in order to facilitate calculation, when the gray level image of the venenum bufonis area at the current moment is analyzed, at least two gray level images of the historical venenum bufonis area acquired before the current moment exist, at this moment, the analysis of the characteristic change of the surface can be ensured, and the moment that the venenum bufonis finishes drying can be avoided.
Preferably, the surface change degree is reflected by extreme value change of the drying characteristic index in the toad venom region gray level image, the maximum value and the minimum value of the drying characteristic index in all the historic toad venom region gray level images are obtained, the whole drying condition of the surface in the corresponding historic time is reflected by the extreme value, the maximum value and the minimum value are taken as a binary group, and different conditions after the surface characteristics of the toad venom are changed from the beginning of drying to the current time are reflected by the binary group.
Calculating the two norms between the binary group of the gray level image of each historical toad venom region and the binary group of the gray level image of the toad venom region at the current moment to obtain characteristic change values, representing the degree of difference of the surface characteristics of the toad venom between each historical moment and the current moment through the characteristic change values, and when the degree of difference gradually becomes stable, namely the smaller the characteristic change values are, indicating that the current moment is closer to the moment of finishing drying. It should be noted that, the method for calculating the two norms is a technical means well known to those skilled in the art, and will not be described herein.
The average value of all the characteristic change values is normalized to obtain a drying change characteristic index of the toad venom region gray level image, and the stability degree of the drying characteristic is judged according to the overall trend of all the characteristic change values, and in the embodiment of the invention, for the accuracy of subsequent calculation, the specific expression of the drying change characteristic index is as follows:
in the method, in the process of the invention,gray scale image of toad venom regionIs characterized by the characteristic index of the drying variation,expressed as the total number of gray scale images of the historic venenum Bufonis area,denoted as the firstExtreme points of gray level images of the historical toad venom areas,gray scale image of toad venom regionIs a boundary between the two points.Represented as a distance function, the euclidean distance is used for calculation in embodiments of the present invention.It should be noted that, normalization is a technical means well known to those skilled in the art, and the normalization function may be selected by linear normalization or standard normalization, and the specific normalization method is not limited herein.
Wherein, the liquid crystal display device comprises a liquid crystal display device,denoted as the firstHistorical toad venom region gray level image and toad venom region gray level imageAfter the average value of all the characteristic variation values is normalized, when the characteristic index of the drying variation is closer to 0, the variation of the surface of the toad venom is more stable, the characteristic variation is close to the processing end point of the toad venom drying, and the gray level image of the toad venom area close to the drying completion can be determined for further analysis.
Preferably, when the characteristic index of the drying variation is smaller than or equal to a preset variation threshold, the fact that the gray level image of the toad venom area at the moment is close to the drying processing end point is indicated, the corresponding gray level image of the toad venom area can be used as a preliminary drying toad venom image, and further refinement analysis is carried out on the preliminary drying toad venom image, so that the processing end point is found more accurately. In the embodiment of the present invention, the preset change threshold is 0.4, and the specific numerical value implementation can be adjusted according to the specific implementation situation.
S4: for the standard image and the preliminary drying toad venom image, obtaining the drying difference degree of the preliminary drying toad venom image according to the difference degree of the drying characteristic indexes corresponding to the detection area; obtaining a drying completion degree according to the drying difference degree and the drying variation characteristic index of the preliminary drying toad venom image; and monitoring and judging the drying state of the toad venom corresponding to the preliminary dried toad venom image according to the drying completion degree.
And (3) for the preliminary dried toad venom image which is near to the processing completion, further judging the drying completion condition of the corresponding toad venom by carrying out the difference degree analysis of the drying characteristics with the standard image, acquiring a standard detection area of the standard image according to the construction method of the detection area, calculating the absolute value of the difference value of the drying characteristic index between the standard detection area and the detection area corresponding to the pixel points at the same position in the preliminary dried toad venom image and the standard image to obtain a characteristic difference value, reflecting the difference condition between the surface characteristics of each local area in the preliminary dried toad venom image and the standard image through the characteristic difference value, and indicating that the surface of the corresponding toad venom is similar to the toad venom after the local area is dried with the standard when the characteristic difference value is smaller.
Taking the accumulated value of all characteristic difference values as the drying difference degree of the preliminary drying toad venom image, reflecting the overall difference between the preliminary drying toad venom image and the standard image through the drying difference degree, and when the difference is smaller, indicating that the surface characteristics of the preliminary drying toad venom image corresponding to the toad venom are closer to the surface characteristics of the toad venom after standard drying, and indicating that the drying state of the corresponding toad venom is closer to the completion drying state. In the embodiment of the invention, the specific expression of the drying difference degree is as follows:
in the method, in the process of the invention,is expressed as a preliminary dried toad venom imageIs used for drying the difference degree of the (5),represented as pixel points in a standard imageCorresponding to the drying characteristic index of the standard detection area,is expressed as a preliminary dried toad venom imageMiddle pixel pointCorresponding to the drying characteristic index of the detection area,represented as the overall length of the abscissa,expressed as the overall length of the ordinate,expressed as abscissa asOrdinate isAnd the pixel points correspond to the positions.Represented as absolute values.
Wherein, the liquid crystal display device comprises a liquid crystal display device,expressed as a standard image and a preliminary dried toad venom imageAt the pixel pointAnd the characteristic difference value at the position is summed up to obtain a drying difference degree, the difference condition of the standard image and the preliminary drying toad venom image is reflected, the smaller the drying difference degree is, the more similar the standard image and the preliminary drying toad venom image are, and the drying state of the toad venom corresponding to the preliminary drying toad venom image is comprehensively analyzed by further combining the drying change characteristic index of the preliminary drying toad venom image.
Preferably, the drying difference degree and the drying variation characteristic index of the preliminary drying toad venom image are multiplied, the product is subjected to negative correlation mapping and normalization processing to obtain the drying completion degree, and the drying completion degree is reflected by multiple indexes through the stable condition of the surface characteristic corresponding to the preliminary drying toad venom image and the standard condition of the surface characteristic, wherein in the embodiment of the invention, the specific expression of the drying completion degree is as follows:
in the method, in the process of the invention,is expressed as a preliminary dried toad venom imageIs used for controlling the drying completion degree of the air conditioner,is expressed as a preliminary dried toad venom imageIs characterized by the characteristic index of the drying variation,is expressed as a preliminary dried toad venom imageIs used for drying the difference degree of the (a).Represented as a normalization function.
When the drying variation characteristic index is smaller, the condition that the variation of the surface characteristics of the toad venom corresponding to the preliminary drying toad venom image is more stable is indicated, the condition is more likely to be a drying completion state, and when the drying variation degree is smaller, the condition that the surface characteristics of the toad venom corresponding to the preliminary drying toad venom image are more similar to those of the standard toad venom, and the condition is more likely to be a drying completion state. Therefore, the characteristic index of the drying variation and the drying difference are in negative correlation with the drying completion, and when the drying completion is larger, the fact that the corresponding toad venom of the preliminary drying toad venom image is closer to the drying completion state is indicated.
After the drying completion degree of the preliminary drying toad venom image is obtained, the drying state judgment of the corresponding toad venom can be carried out according to the drying completion degree. Because the monitoring process is continuous monitoring of the toad venom drying processing process, in judging the drying state, the stable condition of the drying completion degree at the current moment is judged through the continuous moment, preferably, the method acquires the gray level images of the historical toad venom areas corresponding to the two moments before the initial dried toad venom image corresponds to the current moment, and takes the gray level images as the gray level images to be analyzed, calculates the drying completion degree of the gray level images to be analyzed, and judges the stable condition of the drying completion degree at the current moment through the three drying completion degrees.
And calculating the average value of the three drying completion degrees to serve as a state stable value, taking the difference value between the drying completion degree of the preliminary drying toad venom image and the state stable value as a drying state value, wherein the drying state value at the moment can judge whether the drying state of the corresponding toad venom at the current moment reaches the standard ideal state or not, and when the drying state value is smaller, the surface drying condition of the corresponding toad venom is stable and is close to the standard toad venom.
When the drying state value is smaller than the preset drying threshold, the condition that the surface drying condition of the toad venom corresponding to the preliminary drying toad venom image is up to the standard is indicated, the drying state of the toad venom corresponding to the preliminary drying toad venom image is marked as a drying completion state, the drying processing of the toad venom in the drying completion state can be stopped, the drying monitoring is completed, and the toad venom product with better quality is obtained.
In summary, the invention divides the gray level image of the toad venom area into a plurality of detection areas, divides the position areas with the preset area size for each detection area, considers the color detail change of the toad venom surface in different position areas, obtains gray level fluctuation indexes according to the color change degree and the gray level value overall trend of each position area, obtains drying characteristic indexes by all gray level fluctuation indexes, and more comprehensively characterizes the surface characteristics of the toad venom local through two aspects of color and gray level value. Further acquiring a historical toad venom region gray level image, acquiring a stable condition that a drying variation characteristic index reflects the surface characteristic of the toad venom region image according to the difference degree of the drying characteristic index of the historical toad venom region gray level image and the current toad venom region image, determining a preliminary drying toad venom image which is closer to finishing drying, and further accurately analyzing the drying state to acquire a more accurate drying result. The drying difference degree is obtained through the difference of the drying characteristic indexes between the preliminary drying toad venom image and the standard image, the drying completion degree of the preliminary drying toad venom image is obtained by combining the drying change characteristic indexes, the drying surface state is analyzed more carefully, the drying condition of the corresponding toad venom is judged through the drying completion degree, the monitoring of the drying state is more comprehensive and accurate, and the quality of a toad venom product is ensured.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.

Claims (8)

1. A toad gland serous fluid drying monitoring method for toad venom processing, which is characterized by comprising the following steps:
acquiring a toad venom region gray level image and a standard image at the current moment; constructing a detection area with a preset size by taking each pixel point in the toad venom area gray level image as a center, and dividing each detection area into a position area with the preset area size;
obtaining a gray scale fluctuation coefficient of each position area according to the gray scale variation degree of the pixel point in each position area, and obtaining a gray scale fluctuation index of each position area according to the integral trend of the gray scale value in each position area and the corresponding gray scale fluctuation coefficient; obtaining a drying characteristic index of the detection area according to all the gray level fluctuation indexes, wherein the gray level fluctuation indexes and the drying characteristic index are in positive correlation;
acquiring gray level images of all the historical toad venom areas before the current moment, and acquiring a drying variation characteristic index of the toad venom area gray level image according to the variation difference degree of the drying characteristic index for all the historical toad venom area gray level images and the toad venom area gray level image; determining a preliminary dried toad venom image according to the drying variation characteristic index;
for the standard image and the preliminary drying toad venom image, obtaining the drying difference degree of the preliminary drying toad venom image according to the difference degree of the drying characteristic indexes corresponding to the detection area; obtaining a drying completion degree according to the drying difference degree and the drying variation characteristic index of the preliminary drying toad venom image; and monitoring and judging the drying state of the toad venom corresponding to the preliminary dried toad venom image according to the drying completion degree.
2. The method for monitoring the drying of toad gland serum for processing venenum bufonis according to claim 1, wherein the method for obtaining the gray scale fluctuation coefficient comprises the following steps:
obtaining the gray value average value of each pixel point in all the position areas in a preset neighborhood range as the fluctuation value of each pixel point; in each position area, calculating the average value of fluctuation values of all pixel points, and taking the absolute value of the difference value between the fluctuation value of each pixel point and the average value of the fluctuation values as a fluctuation difference value;
and carrying out negative correlation mapping and normalization processing on the accumulated values of all fluctuation difference values in each position area to obtain the gray scale fluctuation coefficient of each position area.
3. The method for monitoring the drying of toad gland serum for processing venenum bufonis according to claim 1, wherein the method for acquiring the gray scale fluctuation index comprises the following steps:
calculating the average value of the gray values of all pixel points in each position area, and taking the average value of the gray values of the inverse proportion as a gray characteristic value; and multiplying the gray characteristic value of each position area with a corresponding gray fluctuation coefficient to obtain a gray fluctuation index of each position area.
4. The method for monitoring the drying of toad gland serum for processing venenum bufonis according to claim 1, wherein the method for acquiring the characteristic index of the drying variation comprises the following steps:
obtaining maximum and minimum values of the drying characteristic indexes in the gray level images of each historical toad venom region, and taking the maximum and minimum values corresponding to the gray level images of each historical toad venom region as a binary group;
calculating the binary norms between the binary group of each historical toad venom region gray level image and the binary group of the toad venom region gray level image to obtain a characteristic change value; and carrying out normalization treatment on the average value of all the characteristic variation values to obtain the drying variation characteristic index of the toad venom region gray level image.
5. The method for monitoring the drying of toad gland serum for processing venenum bufonis according to claim 1, wherein the method for obtaining the drying difference comprises the following steps:
acquiring a standard detection area of a standard image; calculating the absolute value of the difference value of the drying characteristic index between the standard detection area and the detection area at the same position in the standard image and the preliminary drying toad venom image to obtain a characteristic difference value;
and taking the accumulated value of all the characteristic difference values as the drying difference degree of the preliminary drying toad venom image.
6. The method for monitoring the drying of toad gland serum for processing venenum bufonis according to claim 1, wherein the method for obtaining the drying completion degree comprises the following steps:
multiplying the stoving difference degree of the preliminary stoving toad venom image and the stoving change characteristic index, and carrying out negative correlation mapping and normalization treatment on the product to obtain the stoving completion degree.
7. The method for monitoring the drying of toad gland serum for processing toad venom according to claim 1, wherein the monitoring and judging of the drying state of the toad venom corresponding to the preliminary dried toad venom image according to the drying completion degree comprises the following steps:
acquiring historical toad venom region gray level images corresponding to two times before the current time corresponding to the preliminary drying toad venom image, taking the historical toad venom region gray level images as gray level images to be analyzed, and calculating the average value of the corresponding three drying completion degrees in the preliminary drying toad venom image and the gray level images to be analyzed to serve as a state stability value; taking the difference value between the drying completion degree of the preliminary dried toad venom image and the state stability value as a drying state value;
and when the drying state value is smaller than a preset drying threshold value, marking the drying state of the toad venom corresponding to the preliminary drying toad venom image as a drying completion state.
8. The method for monitoring the drying of toad gland serum for processing venenum bufonis according to claim 1, wherein the method for acquiring the preliminary dried toad gland serum image comprises the following steps:
and when the characteristic index of the drying variation is smaller than or equal to a preset variation threshold, taking the corresponding gray level image of the toad venom area as a preliminary drying toad venom image.
CN202310595724.4A 2023-05-25 2023-05-25 Bufo siccus gland slurry drying monitoring method for processing toad venom Active CN116342592B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310595724.4A CN116342592B (en) 2023-05-25 2023-05-25 Bufo siccus gland slurry drying monitoring method for processing toad venom

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310595724.4A CN116342592B (en) 2023-05-25 2023-05-25 Bufo siccus gland slurry drying monitoring method for processing toad venom

Publications (2)

Publication Number Publication Date
CN116342592A CN116342592A (en) 2023-06-27
CN116342592B true CN116342592B (en) 2023-07-25

Family

ID=86886159

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310595724.4A Active CN116342592B (en) 2023-05-25 2023-05-25 Bufo siccus gland slurry drying monitoring method for processing toad venom

Country Status (1)

Country Link
CN (1) CN116342592B (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103301155A (en) * 2013-06-03 2013-09-18 安徽华佗国药股份有限公司 Processing method of venenum bufonis
CN105973858A (en) * 2016-06-13 2016-09-28 宜春学院 Automatic detection system for traditional-Chinese-medicine quality
WO2022089236A1 (en) * 2020-11-02 2022-05-05 腾讯科技(深圳)有限公司 Image processing method apparatus based on artificial intelligence, and computer device and storage medium
CN115601364A (en) * 2022-12-14 2023-01-13 惠州威尔高电子有限公司(Cn) Golden finger circuit board detection method based on image analysis

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9858661B2 (en) * 2013-06-13 2018-01-02 The Charles Stark Draper Laboratory, Inc. Detecting species diversity by image texture analysis

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103301155A (en) * 2013-06-03 2013-09-18 安徽华佗国药股份有限公司 Processing method of venenum bufonis
CN105973858A (en) * 2016-06-13 2016-09-28 宜春学院 Automatic detection system for traditional-Chinese-medicine quality
WO2022089236A1 (en) * 2020-11-02 2022-05-05 腾讯科技(深圳)有限公司 Image processing method apparatus based on artificial intelligence, and computer device and storage medium
CN115601364A (en) * 2022-12-14 2023-01-13 惠州威尔高电子有限公司(Cn) Golden finger circuit board detection method based on image analysis

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于图像处理技术的麦冬药材特征提取与识别;凌秀华;卢文彪;王耐;梁丽金;李熙灿;;辽宁中医杂志(第07期);全文 *

Also Published As

Publication number Publication date
CN116342592A (en) 2023-06-27

Similar Documents

Publication Publication Date Title
CN115018844B (en) Plastic film quality evaluation method based on artificial intelligence
CN116309559B (en) Intelligent identification method for production flaws of medium borosilicate glass
CN117218042B (en) Visual analysis and detection method for hair types
CN106157264B (en) Large area image uneven illumination bearing calibration based on empirical mode decomposition
CN116758077A (en) Online detection method and system for surface flatness of surfboard
CN116612470B (en) Bread detection method and system based on visual characteristics
CN116228772B (en) Quick detection method and system for fresh food spoilage area
CN110852956A (en) Method for enhancing high dynamic range image
CN116205910B (en) Injection molding temperature self-adaptive learning regulation and control system for power adapter
Kundu et al. Visual attention guided quality assessment of tone-mapped images using scene statistics
CN116342592B (en) Bufo siccus gland slurry drying monitoring method for processing toad venom
CN112102238A (en) Method for detecting swelling capacity of starch granules in gelatinization process based on computer vision
CN114972067A (en) X-ray small dental film image enhancement method
WO1994011987A1 (en) Apparatus and method for enhancing color images
CN117541654B (en) Detail enhancement method for high-resolution remote sensing image
Umilizah et al. Combination of Image Improvement on Segmentation Using a Convolutional Neural Network in Efforts to Detect Liver Disease
CN117173049A (en) Image enhancement method for ureteroscope lithotripsy and lithotomy
CN108680535A (en) Based on the spectral reflectance recovery method for improving R matrixes
CN116893134A (en) Method for testing color fastness of jean
Lu et al. An image recognition algorithm based on thickness of ice cover of transmission line
CN103871084B (en) Indigo printing fabric pattern recognition method
CN116077030A (en) Skin evaluation method based on skin component volume content
CN109949279A (en) A kind of Analysis of age system based on skin image
Handayani et al. Determination of beef marbling based on fat percentage for meat quality
Tran et al. Determination of Injury Rate on Fish Surface Based on Fuzzy C-means Clustering Algorithm and L* a* b* Color Space Using ZED Stereo Camera

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant