A modified Hough transform based on a likelihood principle of connectivity and thickness is proposed for line detection. It makes short as well as thick line segments easier to detect in a noisy image. Certain desirable properties of the new method are justified by theory and simulations.

This paper introduces the complex subband transform (CST) that can be applied for both subband signal decomposition and motion estimation, which are the two major processes in subband-based image sequence coding. In the experiments, we compare the CST-based subband motion compensation with conventional block matching motion compensation, and find that the former has (i) higher peak signal-to-noise ratio (PSNR) of the reconstructed images and (ii) lower prediction error entropy of the motion vectors.

This paper presents a sign language recognition system which consists of three modules: model-based hand tracking, feature extraction, and gesture recognition using a 3-D Hopfield neural network. In the experiments, we illustrate that this system can recognize 15 different gestures accurately.