Applications of geostatistics and Markov models for logo recognition
Tuan D. Pham · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Spatial covariances based on geostatistics are extracted as representative features of logo or trademark images. These spatial covariances are different from other statistical features for image analysis in that the structural information of an image is independent of the pixel locations and represented in terms of spatial series. We then design a classifier in the sense of hidden Markov models to make use of these geostatistical sequential data to recognize the logos. High recognition rates are obtained from testing the method against a public-domain logo database.