Semantic classification of business images
Berna Erol, Jonathan J. Hull · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.