Fruit location identification method

Abstract

The invention discloses a fruit location identification method. The fruit location identification method includes that using a neural network color classification model to divide to obtain a fruit pixel region; using an edge detection algorithm to carry out edge detection on a fruit pixel region image without background to obtain the fruit boundary; carrying out Hough transform circle detection on the fruit edge image through a shape locating Hough transform technology in the image to obtain fruit circle and circle center position, and realizing to divide the overlapped region of the fruit; based on image depth information, camera pose information and world position information, using a world coordinate transformation algorithm to extract the world coordinates of the circle center of each fruit to realize the quick detecting, precise locating and precise counting for the fruit.

Description

technical field [0001] The invention relates to the technical fields of computer vision and pattern recognition, and more specifically relates to a fruit positioning and recognition method. Background technique [0002] With the rapid development of global informatization, digital agriculture has developed into a new trend of modern agriculture. Quickly and accurately obtaining image information of crop growth patterns has become an inevitable trend and means of agricultural digitalization and intelligent management. Using machine vision technology to accurately obtain the number of fruits on fruit trees is the key to fruit tree yield measurement and fine orchard management. Traditional fruit yield estimation is based on historical data, weather conditions and manual counting. This method not only has large errors, but also takes time and effort, which can no longer meet the needs of modern agricultural development. With the development of modern information technology, th...

AI Technical Summary

Problems solved by technology

However, this invention does not solve the problems of fruit covering, overlapping, positioning, etc.

[0005] Other related studies are not satisfactory. The existing technology is significantly affected by ambient light, and it cannot solve the problems of light changes, fruit surface color variation, overlap, occlusion, fruit positioning and counting, etc. large error

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