Image recognition based on two-dimensional principal component analysis combining with wavelet theory and frame theory
type: Item
instance of: scholarly article
title: Image recognition based on two-dimensional principal component analysis combining with wavelet theory and frame theory
zbMATH Open document ID: 1400.68192
DOI: 10.1155/2018/9061796
author: Pingping Tao
author: Xiaoliang Feng
author: Chenglin Wen
published in: Journal of Control Science and Engineering
publication date: 2018-12-12T00:00:00Z
review text: Summary: The key to improve the image recognition rate lies in the extraction of image features. In this paper, a feature extraction method is proposed for the images with similar feature in the strong noise background, which is two-dimensional principal component analysis combined with wavelet theory and frame theory. Considering that the image will be influenced by man-made and environmental noises, the algorithm of this paper considers the improvement of many algorithms. Firstly, the images are preprocessed by images enhancement based on feature enhancement. The images are processed by wavelet transform. Then, the preprocessed image matrices are used to obtain the eigenvectors, and the eigenvectors are interpolated with frame, which makes more sufficient information in the frame theory and better extracts the features on the image. Finally, this algorithm is compared other algorithms in the standard ORL face recognition database. The comparison of recognition rate and recognition time by simulation experiment is carried out in order to obtain the validity of the proposed algorithm.
Mathematics Subject Classification ID: 68T10
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 65T60
Mathematics Subject Classification ID: 68U10
zbMATH DE Number: 6992170
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/9061796
OpenAlex ID: W2889993369
cites work: A theory for multiresolution signal decomposition: the wavelet representation
description: scientific article; zbMATH DE number 6992170