VLSI architecture for image transformation

Abstract

Several theorems on image transformations are proved, and new algorithms are proposed to perform these functions. These algorithms perform mapping and filling at the same time, while respecting the connectivity of the original image. As a result, the transformations become more consistent and accurate. The essential parallelism in the new algorithms also facilitates their implementation using VLSI architecture, such that the time complexity is the only O(N) compared with O(N/sup 2/) using a uniprocessor, where n is the dimension of the image plane. The new algorithms can handle all kinds of images, including those of long narrow objects which present problems to other algorithms. They also reduce the errors introduced by the order in which rotation and scaling are applied. A series of experiments was conducted to verify the performance of the proposed algorithms. The results indicate that the new algorithms and VLSI architectures can be very useful to image-processing, pattern recognition, and related areas, especially real-time applications.<>