Cluster-dot Screening by Local Exhaustive Search with Hardware Accelaration

Screening is an important task to convert a continuous-tone image into a binary image with pure black and white pixels. The main contribution of this paper is to show a new algorithm for cluster-dot screening using the local exhaustive search. Our new algorithm generates 2-cluster, 3-cluster, and 4-cluster binary images, in which all dots have at least 2, 3, and 4 pixels, respectively. The experimental results show that it produces high quality and sharp cluster-dot binary images. We also implemented it on an FPGA to accelerate the computation and achieved a speedup factor of more than 200 over the software implementations.