Image Retrieval Based on Multi-features

Kong Fanhui
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引用次数: 4

Abstract

This paper studies the visual feature extraction of image retrieval. According to HSV color space, we quantify the color space in non-equal intervals, construct one-dimensional feature vector and represent the color feature by cumulative histogram. In describing the image texture features, we use the gray-level co-occurrence matrix (GLCM) and Gabor wavelets respectively. Finally, the HSV color features are combined with GLCM and Gabor wavelets respectively for image retrieval. Experiment results show the effectiveness of the algorithm.
基于多特征的图像检索
本文研究了图像检索中的视觉特征提取。根据HSV颜色空间,对非等间隔的颜色空间进行量化,构造一维特征向量,并用累积直方图表示颜色特征。在描述图像纹理特征时,分别使用灰度共生矩阵(GLCM)和Gabor小波。最后,将HSV颜色特征分别与GLCM和Gabor小波相结合进行图像检索。实验结果表明了该算法的有效性。
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