A method for division of litchi fruit picking area based on matlab image processing
A region division method and image processing technology, applied in the direction of instruments, computing, character and pattern recognition, etc., can solve problems such as picking and research without regionalization
Active Publication Date: 2021-09-24
SOUTH CHINA AGRI UNIV
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Problems solved by technology
However, in the process of litchi picking, the vision system of the robot is mostly combined with the manipulator picking, and there is basically no research on regional picking
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[0050] Such as figure 1 As shown, the present embodiment is based on MATLAB image processing litchi fruit picking area division method, specifically comprises the following steps:
[0051] (1) collecting the canopy image of the litchi canopy;
[0052] Use the image acquisition equipment industrial camera to pick and shoot the canopy of lychee to get the image of the canopy.
[0053] (2) Carry out denoising preprocessing to the collected tree canopy image, specifically:
[0054] Step 1: The original fruit image is decomposed into three color images of R, G, and B in the RGB color space, and each color image is a two-dimensional image;
[0055] Step 2: Next, each color image is decomposed into low-frequency and high-frequency parts using a two-dimensional tower decomposition algorithm, and then the low-frequency part and high-frequency part are processed separately using histogram averaging and contrast enhancement;
[0056] Step 3: Merge the processed low-frequency and high-fr...
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The invention discloses a method for division of litchi fruit picking areas based on MATLAB image processing. The fruit picking machinery combined with the regional picking method makes decision-making divisions for its picking. A binocular vision camera is used to photograph litchi tree crowns, identify, locate, and extract coordinates. , The best position to divide the picking area. Use the binocular camera to collect the photos of the crown fruit to analyze the photos and use the color-based K-means clustering and Hough circle transform to detect the suspected fruit area. And use the AdaBoost classifier trained by the local binary pattern features of fruit and non-fruit to detect the suspected fruit area and non-fruit area, and complete the identification of litchi fruit after merging the detection results; after obtaining the coordinate information of litchi, use K-means The clustering method performs clustering analysis on the area, and after classification, the centroid of the divided area of each block is used as the center point of the picking position. The invention relates to the field of machine vision and has important significance for orchard automation.
Description
technical field [0001] The invention belongs to the field of orchard picking, in particular to a decision-making method for litchi orchard picking based on MATLAB image analysis. Background technique [0002] Litchi picking machine has become a research hotspot in the field of agricultural engineering because of its advantages of improving picking efficiency, reducing labor intensity and saving litchi harvesting costs. However, in the litchi picking process, the robot's vision system is mostly combined with the manipulator picking, and there is basically no research on regional picking. To this end, based on theoretical methods such as binocular stereo vision, machine learning, and cluster analysis, this paper conducts in-depth research on the methods of identifying, locating, and picking decisions for litchi fruits in unstructured environments. And use software simulation and hardware test for the recognition and positioning of many types of litchi with different growth fo...
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IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/38G06V10/40G06V10/44G06V10/467G06V20/68G06F18/23213G06F18/2148G06F18/24
Inventor 李君李伯阳潘丽敏郭景达张廷浩李志强
Owner SOUTH CHINA AGRI UNIV