Fruit and vegetable detection method based on deep learning

Abstract

The invention discloses a fruit and vegetable detection method based on deep learning. The method comprises the following steps that: S1: firstly, preprocessing data, and carrying out manual calibration on an original picture in advance to obtain a segmentation tag, wherein the calibration means the coordinates of the left upper angular point and the right lower angular point of a target frame in the original picture, and the tag is used for judging whether a target in each calibration frame is a fruit and vegetable and determining the category of the fruit and vegetable; S2: secondly, training the data, taking the original picture and the picture tag as a training set of a deep learning neural network, and combining with a RPN (Region Proposal Network) and a Fast R-CNN to train the data to obtain a final fruit and vegetable detection model; and S3: finally, testing test data, calling a final fruit and vegetable detection model and a test program, carrying out fruit and vegetable detection on a test picture, and analyzing a final fruit and vegetable detection model effect through the observation of a test result.

Description

technical field [0001] The invention relates to a novel method for detecting fruits and vegetables, specifically through the Faster R-CNN network in deep learning to realize the detection of fruits and vegetables. Background technique [0002] Fruit and vegetable picking is the most time-consuming and labor-intensive link in the agricultural production chain, accounting for about 40% of the entire workload. The quality of picking operations directly affects the storage, processing and sales of fruits and vegetables, which ultimately affects market prices and economic benefits. Therefore, fruit and vegetable picking robots, as a form of agricultural robots, will become an inevitable product of the development of my country's agricultural modernization to a certain stage. As an important part of the picking robot, the vision system is the primary task and design difficulty of the fruit picking robot to identify the fruits and vegetables from the complex background and locate ...

AI Technical Summary

Problems solved by technology

However, because traditional machine vision methods have not yet been effectively resolved in terms of identifying fruits and vegetables from complex backgrounds and determining the spatial position of fruits and vegetables, the results of the currently developed fruit and vegetable picking robots are not ideal, which has become a constraint. Bottlenecks in the Research and Application of Fruit and Vegetable Picking Robots

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