A method for fruit and vegetable recognition in complex environments based on computer vision

Abstract

The invention discloses a method for identifying fruits and vegetables in a complex environment based on computer vision. The method comprises the following steps that firstly, an image of the fruits and vegetables to be identified is obtained; secondly, the obtained image of the fruits and vegetables is pre-processed, and the pre-processed image is divided into a fruit and vegetable area and a background area; the features of the pre-processed image of the fruits and vegetables are extracted, wherein the extracted image features comprise the color features and the texture features; then, the features of the fruits and vegetables are fused through the self-adapting weighting method; finally, the fruits and vegetables are identified through the nearest neighbor sorting algorithm. Compared with an exiting fruit and vegetable identification system, the method for identifying the fruits and vegetables in the complex environment based on the computer vision has the advantages that the algorithm complexity is low, the identification rate is high, a high usability is achieved, and the method can be effectively applied to daily life.

Description

technical field [0001] The invention relates to a method for identifying fruits and vegetables in a complex environment based on computer vision. Background technique [0002] At present, the sales of fruits, vegetables and other products in supermarkets mainly rely on barcodes to obtain product prices. However, since fruit and vegetable products often have to be packaged before they can be labeled with barcodes, this consumes a lot of manpower and material resources. In addition, due to the wide variety of fruits and vegetables , The prices of different fruits and vegetables are different, and various prices mainly rely on artificial memory, which greatly increases the economic and time cost of training personnel in supermarkets. Therefore, a more reasonable and fast solution needs to be proposed. Because of its simplicity and feasibility, the agricultural product detection technology based on computer vision has been widely used in the fields of agricultural product qualit...

AI Technical Summary

Problems solved by technology

[0004] 2. Randomness of fruits and vegetables

[0006] Before the present invention, there were few researches on fruit and vegetable identification in supermarkets both at home and abroad, and there were mainly problems in the following aspects: 1. Practical, low-complexity fruit and vegetable identification algorithms were less

The earliest research on fruit and vegetable recognition in supermarkets can be traced back to 1996. Bolle et al. used color features and texture features to realize the research on fruit and vegetable recognition, and developed the "VeggieVision" system, but the image segmentation and feature extraction technologies used in this system, The feature fusion method is too old. The feature extraction method needs to use a high-volume convolution operation. The feature fusion part has not been studied in depth, and the fruit and vegetable recognition rate of the system is low; 2. The high-complexity algorithm is not practical

The research on fruit and vegetable recognition in supermarkets did not start to be published in the literature until 2008. However, at this time, most of the algorithms for fruit and vegetable recognition research focused on the theoretical aspect, and the feature recognition extraction algorithm, feature fusion algorithm, and classifier algorithm used Most of them are high-complexity algorithms. The feature extraction methods used in some literatures are not practical due to the high complexity of the algorithms.

Images