颜色直方图
颜色量化
人工智能
数学
颜色深度
颜色归一化
模式识别(心理学)
彩色图像
HSL和HSV色彩空间
色空间
计算机视觉
图像渐变
色调
直方图
色彩平衡
精确性和召回率
计算机科学
图像处理
图像(数学)
病毒
病毒学
生物
作者
Raymond Phan,Dimitrios Androutsos
标识
DOI:10.1016/j.cviu.2009.07.004
摘要
In this paper, we present an algorithm that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme on compound color objects, for the retrieval of logos and trademarks in unconstrained color image databases. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, as compared to the simple color pixel difference classification of edges seen with the CECH. Our proposed method is thus reliant on edge gradient information, and so we call it the Color Edge Gradient Co-occurrence Histogram (CEGCH). We also introduce a color quantization method based in the hue–saturation–value (HSV) color space, illustrating that it is a more suitable scheme of quantization for image retrieval, compared to the color quantization scheme introduced with the CECH. Experimental results demonstrate that the CEGCH and the HSV color quantization scheme is insensitive to scaling, rotation, and partial deformations, and outperforms the use of the CECH in image retrieval, with higher precision and recall. We also perform experiments on a closely related algorithm based on the Color Co-occurrence Histogram (CCH) and demonstrate that our algorithm is also superior in comparison, with higher precision and recall.
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