Improved texture feature extraction algorithm based on Radon transform

Abstract

The invention discloses an improved texture feature extraction algorithm based on Radon transform, and relates to the technical field of digital image processing. The improved texture feature extraction algorithm comprises the Radon transform, dual-tree complex wavelet transform, extraction of sub-band coefficients, calculation of characteristic values, construction of characteristic vectors, and calculation of similarity; the Radon transform performs Radon transform on an original image, and extracts rotation invariants through a relationship between an image Radon domain coefficient and an image rotation angle; the dual-tree complex wavelet transform performs transform on a projection matrix obtained after the transformation; the extraction of the sub-band coefficients, the calculation of the characteristic values and the construction of the characteristic vectors are carried out on the basis of the dual-tree complex wavelet transform; and the calculation of the similarity is calculated based on the Euclidean distance between an input image and an image texture feature vector in an image database, and an image matched with a target image is retrieved. The improved texture feature extraction algorithm based on the Radon transform provided by the invention solves the problem that the movement or rotation of the image influences the generated wavelet transform coefficients, so that image retrieval is convenient and efficient.

Description

Technical field [0001] The invention relates to the technical field of digital image processing, in particular to an improved texture feature extraction algorithm based on Radon transform. Background technique [0002] In criminal investigation and traffic accident investigation, the image is regarded as an important clue. Image retrieval is very important for the police to quickly find useful target images in the database. Although many algorithms have been designed to extract image features, Few studies have been done on image retrieval with a certain degree of rotation. [0003] Texture feature is one of the important features of image features. It can be described in the time domain or in the frequency domain. The Tamura texture feature and the gray-level co-occurrence matrix are typical texture feature extraction algorithms in the time domain, Fourier transform and Wavelet transform is a typical texture feature extraction algorithm in the frequency domain. [0004] Wavelet tra...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide an improved texture feature extraction algorithm based on Radon transform, which is reasonable in design, solves the problem of the influence of image movement or rotation on the generated wavelet transform coefficients, and facilitates image extraction. search, convenient and efficient

Images