Image binarization using iterative partitioning: A global thresholding approach

Abstract

This paper proposes a new method for image binarization. This is a modified and improved version of the iterative partition based algorithm proposed in [1]. The proposed method has been compared with other five representative binarization methods including the algorithm proposed in [1]. The USC-SIPI image database has been used for experimental verification purposes. The results of implementation of the algorithms unearth the superiority of the proposed method compared to the other five methods in terms of two quantitative measures, namely, misclassification error and the relative foreground area error.