Picture-graphics color image classification
S. Prabhakar, Hui Cheng, John C. Handley, Zhigang Fan, Yingwei Lin · Proceedings - International Conference on Image Processing · 2003
High-level (semantic) image classification can be achieved by analysis of low-level image attributes geared for the particular classes. In this paper, we have proposed a novel application of the known image processing and classification techniques to achieve such a high-level classification of color images. Our image classification algorithm uses three low-level image features: texture, color, and edge characteristics to classify a color image into two classes: business graphics or natural picture. We have achieved an accuracy of 96.6% on our database of 209 images using a combination of tree and neural network classifiers.