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Abalone body type parameter image measurement method

A technology of image measurement, abalone, applied in the field of computer vision

Active Publication Date: 2020-09-29
XIAMEN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to provide an image measurement method for abalone body parameters that can solve problems such as automatic image measurement of abalone

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  • Abalone body type parameter image measurement method
  • Abalone body type parameter image measurement method
  • Abalone body type parameter image measurement method

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Embodiment Construction

[0041] In order to further elaborate on the technical features and advantages of the present invention, the following embodiments will further illustrate the present invention in conjunction with the accompanying drawings.

[0042] Such as figure 1 As shown, the present embodiment provides an image measurement method of abalone body parameters, and the specific steps are as follows:

[0043] Step 1, first collect and label the abalone dataset. Each abalone data sample contains abalone and a reference ruler. When labeling abalone, use the labelme labeling software to mark the abalone and the ruler. At the same time, the length, width and weight of the abalone were manually measured, and the data set was divided into a training set and a data set according to a ratio of 1:1.

[0044] Step 2. Use the YOLOV3 target detection algorithm to train the training data set. The model initialization uses the ImageNet pre-training model. The uniform size of the image input is 416*416, tr...

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Abstract

The invention discloses an abalone body type parameter image measurement method, and belongs to the technical field of computer vision. The method comprises the following steps: collecting an abalonedata set, training the data set by using a YOLOV3 target detection algorithm, detecting a target abalone and a reference object ruler, and cutting out a target prospect; obtaining abalone edges by using a canny operator, and calculating the minimum bounding rectangle frame of the edges and the area covered by the edges; performing scale calculation on the straight ruler to obtain a proportion between the pixel value and the scale; converting the length and width of the minimum rectangle into the actual length and width to obtain the length and width of the abalone; performing feature combination through the length, the width and the area occupied by the abalone, training a GBDT algorithm model to obtain an abalone weight prediction model, inputting the detected length, width and area features, and outputting the abalone weight. After the YOLOV3 detects the target, prediction can be carried out by combining a GBDT model. The length, the width and the weight of the abalone can be automatically detected, and the labor cost and the time cost are greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to an image measurement method for abalone body shape parameters. [0002] technical background [0003] Abalone is a very common marine life, not only delicious, but also has high nutritional value, and is deeply loved by consumers. Many factories process abalones as food, and abalones are differentiated by size. In many cases, manual sorting is performed based on the experience of workers. It is difficult for an inexperienced worker to sort quickly and correctly, so there is a need Low efficiency, inaccurate sorting and other problems. In the field of scientific research, scientists need a large amount of data sets when conducting research on abalone, and the measurement of these abalone data is basically marked by manual measurement, which takes up a lot of manpower and time, which is not good for scientific research. An important concern, not great value for...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/13G06T7/136G06T7/62G06N3/08
CPCG06T7/0004G06T7/13G06T7/136G06T7/62G06N3/08G06T2207/20081G06T2207/20084G06T2207/30128
Inventor 刘向荣彭惠民柳娟张悦
Owner XIAMEN UNIV