Knowledge-Based Silhouette Detection
Antonio Fernández‐Caballero · 2005
Abstract. A general-purpose neural model that challenges image understanding is presented in this paper. The model incorporates accumulative computation, lateral interaction and double time scale, and can be considered as biologically plausible. The model uses- at global time scale t and in form of accumulative computation- all the necessary mechanisms to detect movement from the grey level change at each pixel of the image. The information on the detected motion is useful as part of an object’s shape can be obtained. On a second time scale base T<