Navel Orange Blemish Identification for Quality Grading System
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
A 2-phase 2-D thresholding algorithm
Digital Signal Processing
Review: Pulse coupled neural networks and its applications
Expert Systems with Applications: An International Journal
Computational Intelligence and Neuroscience
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Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise ratio than one-dimensional (1D). But it gives satisfactory results only when the numbers of pixels in each class are close to each other. Otherwise, it gives the improper results. In this paper, 2D histogram projection is used to correct the Otsu threshold. The 1D histograms are acquired by 2D histogram projection in x and y axes and a fast algorithm for searching the extrema of the projected histogram is proposed based on the wavelet transform in this paper. Experimental results show that the proposed method performs better than the traditional Otsu method for our renal biopsy samples.