Useful Image Transform Coefficients For Pattern Recognition

The problem of recognition of objects in images is investigated from the simultaneous viewpoint of image bandwidth compression and automatic target recognition. A hypothetical scenario is suggested in which recognition is implemented on features in the block cosine transform domain which is useful for data compression as well. Useful features from this cosine domain are developed based upon correlation parameters and homogeneity measures which appear to successfully discriminate between natural and man-made objects. The Bhattacharyya feature discriminator is used to provide a 10:1 compression of the feature space for implementation of simple statistical decision surfaces (Gaussian classification).© (1978) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.