Image Segmentation Based on Framework of Two-dimensional Histogram and Class Variance Criterion
Fangyan Nie, Pingfeng Zhang · International Journal of Signal Processing Image Processing and Pattern Recognition · 2015
Histogram thresholding is one of the most popular image segmentation techniques.Variance-based thresholding is a famous method in which.In this paper, a new method based the framework of two-dimensional gray level histogram and class variance criterion is proposed.The methodology for image segmentation using two-dimensional histogram and variance criterion is elaborated firstly.Then the algorithm of the presented scheme is realized through recursion.Finally, the proposed method is tested on synthetic and real-world images.Experimental results show that the proposed method is better to overcome the shortcomings of the conventional variance-based methods, and the effectiveness of the proposed method is demonstrated by the experiments.