Volume 36, Number 4, August 2018
|Page(s)||742 - 747|
|Published online||24 October 2018|
Research of Image Retrieval Method Based on Improved Feature
School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
In the process of image retrieval, the traditional single feature can't reflect the distribution and details of image color and content, which have some adverse influence on the performance of image retrieval. This paper presents an image retrieval method based on improved color and texture feature. According to the mean of the HSV color model region, algorithm obtains the mean eigenvectors of the color feature by using the improved correlation weight model. The image decomposition transformation is obtained through the Haar wavelet. In the low-frequency component of the image decomposition, the low-frequency texture feature vector is obtained according to the low-frequency feature structure model. The similarity of image is calculated by the Canberra distance. Experimental results show that:the methods of retrieval are tested in Corel-1000 and Corel-5000 standard gallery, which accuracy rate and retrieval rate have been improved accordingly.
Key words: image retrieval methods / improve color average feature / improved iow frequency texture feature / similarity / MATLAB
关键字 : 图像检索 / 改进颜色均值特征 / 改进低频纹理特征 / 相似度
© 2018 Journal of Northwestern Polytechnical University. All rights reserved.
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