Image retrieval based on chrominance feature of the HMMD color space

L. Pavithra, T. Sharmila
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Abstract

This paper proposes a new chrominance feature extraction method in HMMD color space. Image dependent multi-level thresholding is performed in the HMMD color space to obtain the 64-IeveI quantized images. The occurrence count of each color pixel represents the color information of those quantized images. This technique is tested over Wang's database of 10 different category images. The distance measure of this feature between the query and database image are calculated. Then, the proposed method performance is evaluated using average precision and recall. Moreover, the proposed method is a benchmark against the state-of-the-art color feature extraction methods and gives approximately 6.3% to 18.05% and 7.54% to 14.52 % high precision and recall than the conventional techniques.
基于HMMD色彩空间色度特征的图像检索
提出了一种在HMMD色彩空间中提取色彩特征的新方法。在HMMD色彩空间中进行图像依赖的多级阈值分割,得到64级量化图像。每个颜色像素的出现次数代表这些量化图像的颜色信息。这项技术在Wang的10个不同类别图像的数据库上进行了测试。计算该特征在查询和数据库图像之间的距离度量。然后,用平均查准率和查全率对该方法的性能进行了评价。此外,该方法是最先进的颜色特征提取方法的基准,与传统技术相比,其精度和召回率分别为6.3% ~ 18.05%和7.54% ~ 14.52%。
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