A Discriminant Analysis Based Recursive Automatic Thresholding Approach for Image Segmentation

Abstract

In this study, we have proposed an efficient automatic multilevel thresholding method for image segmentation. An effective criterion for measuring the separability of the homogenous objects in the image, based on discriminant analysis, has been introduced to automatically determine the number of thresholding levels to be performed. Then, by applying this discriminant criterion, the object regions with homogeneous illuminations in the image can be recursively and automatically thresholded into separate segmented images. The proposed method is fast and effective in analyzing and thresholding the histogram of the image. In order to conduct an equitable comparative performance evaluation of the proposed method with other thresholding methods, a combinatorial scheme is also introduced to properly reduce the computational complexity of performing multilevel thresholding. The experimental results demonstrated that the proposed method is feasible and computationally efficient in automatic multilevel thresholding for image segmentation.