Image segmentation on a 2D array by a directed split and merge procedure
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Image segmentation can be performed by recursively splitting the whole image or by merging together a large number of minute regions until a specified condition is satisfied. The split and merge procedure of image segmentation takes an intermediate level in an image description as the starting cutset and thereby achieves a compromise between merging small primitive regions and recursively splitting the whole image in order to reach the desired final cutset. The choice of the initial cutset offers significant savings in computation time. A 2D array implementation of image segmentation by a directed split and merge procedure has been proposed in this paper. Parallelism is realized on two levels: One within the split and merge operations, where more than one merge (or split) may proceed concurrently, and the second between the split and merge operations, where several splits may be performed in parallel with merges. Both the split and merge operations are based on nearest neighbor communications between the processing elements (PEs) and therefore facilitate low communication costs. The basic arithmetic operations required to perform split and merge are comparison and addition. This allows a simple structure of the PE as well as a hardwired control. A local memory of 512 bytes is sufficient to hold the interim data associated with each PE. A prototype of the PE has been constructed using the 3-pm double metal CMOS technology. Considering a scaling for up to 0.8 pm, it is possible to incorporate 16 PEs on a 256 cm2 chip. With sufficiently large PE window sizes, image segmentation through the proposed approach can be achieved in linear time. 1992 IEEE
