Graphics/Image Retrieval Method

New computing technologies, media acquisition/storage devices, and multimedia compression standards have increased the amount of digital data generated and stored by computer users. Nowadays, it is easy to access electronic books, electronic journals, and web portals, which contain tremendous graphics (drawings or diagrams) and images (pictures or scenery). Hence, it is imperative to develop an effective graphics/image retrieval method. In particular, when users have photos that may contains graphics or images, they want to access electronic database to retrieve related information. Although many content-based retrieval methods have been developed for images and graphics, few are specifically designed for graphics and images simultaneously. Moreover, most existing graphics retrieval methods use contour-based rather than pixel-based approaches. A contour-based method is concerned with a lot of lines or curves which is not proper for image retrieval. Thus, the objective of this study was to develop simple yet effective graphics/image retrieval using pixel-based features. The proposed method uses histograms of oriented gradient (HOG) as pixel-based features. However, the characteristics of graphics and images differ, and this affects feature extraction and retrieval accuracy. Thus, an adaptive method is proposed to select different HOG-based features for retrieving graphics and images with high retrieval accuracy. Experimental results confirm that the proposed method has high retrieval accuracy.