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Cotton detection, segmentation and counting method and system

A counting method and cotton technology, applied in the field of computer vision recognition, can solve the problems of flexibility in difficult application scenarios, low recognition rate, large model size, etc., and achieve the effect of avoiding repeated operations, good robustness, and improving effect.

Active Publication Date: 2021-08-24
SHANDONG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The current traditional methods of cotton segmentation and detection and positioning have the problems of low recognition rate and poor robustness, while the depth method has problems such as large model size and difficulty in flexible deployment in actual application scenarios.

Method used

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  • Cotton detection, segmentation and counting method and system
  • Cotton detection, segmentation and counting method and system
  • Cotton detection, segmentation and counting method and system

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0063] Embodiment 1 of the present invention provides a cotton detection, segmentation and counting system, the system includes:

[0064] The segmentation module is used to combine the color features, calculate the h channel histogram, obtain the mask image matrix of the image background and the foreground, initialize the grabCut algorithm, and perform segmentation;

[0065] The extraction module is used to perform preliminary morphological processing on the segmented picture, filter out smaller areas, and fill closed holes in the area, and extract the relevant attributes of each connected domain;

[0066] The merging module is used for region merging, and for two connected domains that meet the conditions, it is merged into one region;

[0067] The splitting module is used for region splitting, splitting the connected domain whose area is greater than the preset first area threshold and the ratio of the long-short axis is greater than the preset long-short axis ratio threshol...

Embodiment 2

[0104] In order to improve the segmentation and detection effect of white cotton in the mature stage under natural field conditions, this embodiment 2 provides a white cotton segmentation, detection and counting method based on color and morphological characteristics, which can further improve the efficiency, speed and efficiency of cotton segmentation and detection and counting. robustness.

[0105] Such as figure 1 As shown, the method described in Embodiment 2 can be roughly divided into 4 steps:

[0106] Step 1. Combining the color features, calculate the h-channel histogram, obtain the mask image matrix of the image background and foreground, initialize the grabCut algorithm, and perform segmentation.

[0107] Step 2. Perform preliminary morphological processing on the segmented image, filter out smaller areas, and fill in small closed holes in the area, and then extract the relevant attributes of each connected area.

[0108] Step 3, region merging, for two connected reg...

Embodiment 3

[0144] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium includes instructions for executing a cotton detection, segmentation and counting method, the method includes:

[0145] Combining the color features, calculate the h-channel histogram, obtain the mask image matrix of the image background and foreground, initialize the grabCut algorithm, and perform segmentation;

[0146] Perform preliminary morphological processing on the segmented image, filter out smaller areas, fill in closed holes in the area, and extract the relevant attributes of each connected domain;

[0147] Region merging, for two connected domains that meet the conditions, merge them into one region;

[0148] Region splitting, splitting a connected domain whose area is greater than the preset first area threshold and whose ratio of the long and short axes is greater than the preset ratio threshold of the long an...

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Abstract

The invention provides a cotton detection, segmentation and counting method and system, and belongs to the technical field of computer vision, and the method comprises the steps: obtaining a mask pattern matrix of an image background and a foreground, initializing a grabCut algorithm, and carrying out the segmentation; performing morphological processing, and extracting related attributes of each connected domain; combining the two connected domains meeting the condition into one region; for the connected domain whose area is larger than a preset first area threshold value and the ratio of the long axis to the short axis is larger than a preset threshold value of the ratio of the long axis to the short axis, dividing the connected domain into two independent areas; and performing cotton counting on the split single connected domain. According to the method, the accuracy is ensured while the model is kept light in volume, rapid and convenient to deploy; the segmentation effect of the algorithm is improved, and the efficiency of the subsequent merging and splitting processing process is improved; repeated operation is avoided, and the merging speed is increased; length detection does not need to be carried out on positions such as a bottleneck in the splitting process, it is guaranteed that the detected position with the highest brightness belongs to the two areas, and robustness is good.

Description

technical field [0001] The invention relates to the technical field of computer vision recognition, in particular to a method and system for detecting, segmenting and counting white cotton based on color and shape features. Background technique [0002] Cotton is one of the most important economic fiber crops in the world, accounting for nearly 80% of the world's total natural fiber production, and white cotton at maturity can be said to be the most important phenotypic trait for predicting cotton fiber production, and the number of cotton bolls is also an indicator of fiber production. an important indicator. [0003] The segmentation and positioning detection of white cotton and the statistics of boll number can not only better understand the physiological and genetic mechanism of crop growth and development, but also serve as an important indicator for predicting yield potential and evaluating crop growth status, which is helpful for making timely crop management decision...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/187G06T7/62
CPCG06T7/0002G06T7/11G06T7/187G06T7/62G06T2207/30242
Inventor 杨公平张岩孙启玉李广阵褚德峰张同心
Owner SHANDONG UNIV
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