Abstract
We propose an approach for detecting logos in document images with complex backgrounds. The detection works with documents that contain non-logo images and are subjected to noise, translation, scaling and rotation. The methods are based on the mountain clustering function, geostatistics and neural networks. The proposed logo detection system is tested with many logos embedded in document images, and the results demonstrate the effectiveness of the approach. It is also more favorable when compared with other existing methods for logo detection. The learning algorithm described herewith can be useful for solving general problems in image categorization.