Robust color texture retrieval method using co-occurrence matrix of pattern spectrums

Shota Takei, S. Wada
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引用次数: 0

Abstract

In this paper, we propose a robust color texture image retrieval method using co-occurrence matrix of pattern spectrums (PSs). The proposed method has robustness to geometric distortions such as shift, rotation, scaling, skew, projection and their combinations. The feature of texture pattern and color is extracted as co-occurrence matrix of PSs of multiple component planes that can be robust to geometric distortion. To realize efficient calculation, binary pattern of RGB components are combined with grey level luminance component to obtain feature vector. In simulations, performance of the proposed method is analyzed under various distortion conditions with similar image retrieval system. Effectiveness is verified by evaluating retrieval accuracy rates. Retrieval accuracy is examined with multi-level as well as binary planes.
基于模式谱共现矩阵的鲁棒彩色纹理检索方法
本文提出了一种基于模式谱共现矩阵的鲁棒彩色纹理图像检索方法。该方法对移位、旋转、缩放、倾斜、投影及其组合等几何畸变具有较强的鲁棒性。将纹理图案和颜色特征提取为多分量平面ps的共现矩阵,对几何畸变具有鲁棒性。为了实现高效的计算,将RGB分量的二值模式与灰度亮度分量结合得到特征向量。在仿真中,用相似的图像检索系统分析了该方法在不同失真条件下的性能。通过评估检索准确率来验证有效性。检索精度在多级平面和二元平面上进行了检验。
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