A Fast 2D Otsu Thresholding Algorithm Based on Improved Histogram

Abstract

Otsu adaptive thresholding is widely used in classic image segmentation. Two-dimensional Otsu thresholding algorithm is regarded as an effective improvement of the original Otsu method. To reduce the high computational complexity of 2D Otsu method, a fast algorithm is proposed based on improved histogram. Two-dimensional histogram is projected onto the diagonal, which forms 1D histogram with obvious peak and valley distribution. Then two-dimensional Otsu method is applied on a line that is vertical to the diagonal to find the optimal threshold. Furthermore, three look-up tables are utilized to improve the computational speed by eliminating the redundant computation in original two-dimensional Otsu method. Theoretical analysis and experimental simulation show that the proposed approach greatly enhances the speed of thresholding and has better immunity to salt and pepper noise.