Improved Edge Detection by the Evaluation of ColorContrast Information

Abstract The IMA Research Group has developed an active vision system, called NAVIS, which is mainly based on neural models. It can roughly be separated into five functional components: camera control, form detection, attractivity calculation, attention selection, and object recognition. The form module initially consisted of a gray value channel for the computation of luminance contrast. In this paper we describe the extension of the gray value channel by two color opponent channels which contribute to the extraction of edges. With these new channels it is possible to detect isoluminant edges. Furthermore, our model achieves a new estimation of the edges caused by luminance and color contrast. The attention and recognition capabilities of NAVIS can be improved by this method as experimental results show.