Image recognition and classification method and device and computer readable storage medium

Abstract

The invention discloses an image recognition and classification method and device and a computer readable storage medium, and the method comprises the steps: obtaining and inputting an original image,carrying out the preprocessing of the original image, and obtaining a preprocessed image; extracting a feature matrix in the preprocessed image, and constructing a training sample according to the feature matrix; inputting the training sample into fuzzy Fisher linear discrimination for training to obtain a projection direction of linear discrimination; and recognizing and classifying the test sample according to the projection direction of the linear discrimination. According to the technical scheme of the invention, the method can achieve the recognition and classification of images, achieves the better expression of image features, improves the accuracy of image classification, and effectively improves the effect and robustness of image classification.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image recognition and classification method, device and computer-readable storage medium. Background technique [0002] Compared with text, images can provide more vivid, easy-to-understand and more artistic information, and are an important source of information for people to transfer and exchange. Image classification is to distinguish different types of images according to the semantic information of images. It is an important basic problem in computer vision and the basis of other high-level visual tasks such as image detection, image segmentation, object tracking, and behavior analysis. Image classification is widely used in many fields, including image recognition, target detection, face recognition and intelligent video analysis in the security field, traffic scene recognition in the traffic field, content-based image retrieval in the Internet field, an...

AI Technical Summary

Problems solved by technology

The traditional Fisher linear discriminant method is widely used in image classification and recognition. The traditional Fisher linear discriminant method mainly completes classification and recognition by extracting feature vectors, but the extraction of image features is often affected by illumination changes, noise, viewing angle, etc. It will cause the accuracy and stability of image feature classification to decline, and the use of feature vectors often cannot express image features well. Therefore, it is necessary to study a method to improve the effect and robustness of image classification

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