• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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Color texture features extraction based on quaternion Gabor

MENG Bo1,WANG Xiaolin1,LI Dongwei2   

  1. (1.School of Information Engineering,Northeast Electric Power University,Jilin 132012;
    2.Vehicle Workshop,Ministry of Railways of the Jilin Petrochemical Co.,PetroChina Co. Ltd.,Jilin 132012,China)
  • Received:2017-06-07 Revised:2017-08-15 Online:2018-09-25 Published:2018-09-25

Abstract:

Current color texture feature extraction methods transform color images into gray images or process color image by channel separation, which can lead to color information loss of the original image or correlation loss between channels, so that the texture feature of the feature image differs greatly from that of the original image. To solve the above mentioned problems, we propose a quaternion Gabor method to extract color texture features. Firstly, quaternion Gabor filter is deduced according to traditional Gabor filter and quaternion Euler’s formula, and the color image is described by Quaternion field. Secondly, we propose a quaternion Gabor convolution algorithm to process the color image, and obtain a multiscale, multidirection color texture image. Finally, Tamura statistical feature is extracted from the color texture image. Experimental results show that the proposed method can maintain text features of the original image such as coarseness, contrast and directionality to a great extent and meanwhile obtain color information, which outperforms the traditional Gabor feature image and LBP method.
 

Key words: color texture, feature extraction, quaternion, Gabor filter