Learning Patterns in Images
Ryszard S. Michalski, Azriel Rosenfeld, Zoran Đurić, Marcus A. Maloof, Qi Zhang · 2002
This chapter concerns problems of learning patterns in images and image sequences, and using them for interpreting new images. The chapter concentrates on three problem areas: (i) semantic interpretation of color images of outdoor scenes, (ii) detection of blasting caps in x-ray images of luggage, and (iii) recognizing actions in video image sequences. It discusses the image formation processes in these problem areas, and the choices of representation spaces used in our approaches to solving these problems. The results presented indicate the advantages of applying machine learning to vision. 10.1 INTRODUCTION The underlying motivation of this research is that vision systems need learning capabilities for handling problems for which algorithmic solutions are unknown or difficult to obtain. Learning capabilities can also make vision systems more easily adaptable to different vision problems, and more flexible and robust in handling variable perceptual conditions [MRA94]. Much of the cur...