Several low-level vision algorithms have been implemented on a 16-node hypercube processor (AMETEK S-14) by exploitation of its network embedding feature. This includes edge detection with the Sobel operator, histogramming, one-pass parallel binary image thinning, and noise-cleaning. The primary objective is to parallelize these algorithms by achieving a proper image-to-processor topology mapping and to determine the actual speedup factor of parallel implementation over the sequential programming. Two basic topologies used are the ring and the nearest-neighbor networks, which are mapped onto the hypercube system.