Automatic Browsing of Large Images on Small Display

In this paper, we propose an automatic image browsing method based on image categorization to effectively browse high-resolution images on small-display-devices such as cellular phones and digital cameras. Based on face detection algorithm and spectrum analysis, input images are categorized into face images and non-face images. The non-face images are again categorized into close-up view images and non-close-up view images. For the non-close-up view images, we conduct further classification into images-with-vanishing-point and images-without-vanishing-point. In the face images case, the browsing path is determined by face locations. In images with vanishing point case, the path is decided along the vanishing lines, while in case of images without vanishing point, we detect the saliency regions using color variance and edges, and the browsing route is determined by the location of saliency regions. We estimate the accuracy of the proposed image classification algorithm through experiments. Subjective evaluation is also conducted to assess the proposed system for automatic image browsing. Experimental results indicate that our system increases viewing satisfaction to small-display viewers.