Fast facet edge detection in image sequences using vector quantization

This paper presents an application that uses vector quantization (VQ) to speed up the process of gradient magnitude edge detection for image sequences. Because image VQ and this type of edge detection operate on block-based neighborhoods, it is possible to use VQ to perform the edge detection. The image is encoded with a VQ for which the edge/no edge decision has already been made for each block. The process of edge detection becomes a simple lookup of this information. The algorithm behaves as a "trainable edge detector" which has the advantage of having lower computational complexity than the facet edge detector. For a VQ with an average rate of 6 bits per vector, our method requires 55% of the multiplications and and 62% of the additions of the conventional facet edge detector. It also enhances the quality of the output by rejecting low contrast, high frequency texture edges.