COntent-based unconstrained logo and trademark retrieval in color image databases with Color Edge Gradient Co-occurrence Histograms

In this paper, we present a logo and trademark retrieval system for general, unconstrained, color image databases, extending the color edge Co-Occurrence Histogram (CECH) object detection scheme. 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, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, thus we call it the Color Edge Gradient Co-occurrence Histogram (CEGCH). We also introduce a novel color quantization scheme based in the Hue-Saturation-Value (HSV) color space, illustrating that it is more suitable for image retrieval in comparison to the color quantization scheme introduced with the CECH. Results illustrate that our retrieval system retrieves logos and trademarks with good accuracy, outperforming the use of the CECH in image retrieval with higher precision and recall.