A region segmentation method for naturally placing grape bunch pedicel by machine vision

Abstract

A region segmentation method for naturally placing grape bunch pedicel by machine vision is provided. A binocular vision system is constructed by adopting a multi-degree-of-freedom bracket, and that irradiation mode of diffuse reflective light source is designed to obtain grape bunch image, Then, the image is decomposed in HSI model, the circular convolution kernel with radius of 3 pixels is designed, the median filter is carried out pixel by pixel along the grape string image, and the LOG kernel function is used to sharpen the edge of the grape string image. Then, based on the distribution characteristics of grape edge region, the minimum distance between disconnected domains in the minimum neighborhood is used to represent the edge distance of grape, According to the distribution histogram of edge distance, the segmentation points of stem edge and kernel edge of grape bunch are obtained, and the morphological kernels of open and close are designed by using the segmentation points ofedge distance, and the morphological operation is carried out by using the adaptive convolution check image. Finally, the high precision and high efficiency segmentation of naturally placing grape bunch pedicel region is realized by machine vision.

Description

technical field [0001] The invention relates to the field of image segmentation based on machine vision, in particular to a method for segmenting fruit stem regions based on machine vision and image processing for naturally placed grape bunches, which is used for automatic sorting by robots. Background technique [0002] In recent years, my country's fruit production has grown rapidly, and traditional manual sorting methods have been difficult to meet the needs of modern agricultural production. Automatic fruit sorting based on robotic technology is of great importance to the automation, scale, and precision development of agricultural production and agricultural product processing. significance. In the robot-based automatic fruit sorting process, the accurate positioning of the grasping point is the prerequisite for the robot to achieve accurate, fast and non-destructive grasping control. Due to the advantages of non-contact, strong applicability, and high cost performance,...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the irregular distribution of fruit stalks and fruit grains of naturally placed grape bunches, and the variety of grape bunch shapes, resulting in low precision and long time-consuming segmentation of the fruit stalk area in the image, the invention proposes a machine vision based on edge distance and automatic segmentation. Segmentation method of naturally placed grape bunch stem region based on morphology

Next, aiming at the problem that the existing morphological methods with fixed convolution kernels are difficult to achieve accurate segmentation of grape stems in naturally placed areas, a stem segmentation method that can adaptively select the size of the convolution kernel is proposed

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