Automatic Thresholding Technique Using Reconfigurable Hardware

Abstract

This research presents an efficient automatic thresholding technique based on Otsu’s method that can be used in edge detection algorithms and then applied as a plug-in for real-time image processing devices. The proposed thresholding technique uses an iterative clustering based method that targets a reduced number of operations. It is well known that the Otsu calculates the global threshold splitting the image into two classes, foreground and background, and choose the threshold that minimizes the interclass variance of the threshold black and white pixels. In this paper, a faster version of Otsu’s method is proposed knowing that the only pixels that have to be moved from one class to another class are the ones with values in between the previous two thresholds. This procedure yields the same set of thresholds as the original method but the redundant computation has been removed and, in this way, only few operations are required. The proposed thresholding technique has been implemented in software using C# programing language and in reconfigurable hardware on a Spartan 3E XC3S500E FPGA board using VHDL. The results obtained, presented for different digital images, confirm that the proposed iterative thresholding algorithm and architecture on FPGA can achieve the requirements to be included in real-time image processing systems.