The purpose of image thresholding according to the gray level pixel collection of a divided

 Image thresholding is one of the most commonly used is the most simple image segmentation method, it is especially suitable for the target and background occupy different gray-scale range of the image. It not only can greatly compress the amount of data, but also greatly simplifies the analysis and processing steps, in many cases, image analysis, feature extraction and pattern recognition before the necessary image pre-processing process.
The purpose of image thresholding according to the gray level pixel collection of a divided, each subset of the formation of a region corresponding to the realistic scenery, each within the region consistent with the properties of adjacent regional distribution of this a consistent attribute. This division can select one or more threshold starting from the gray level. The consumers of the cufflinks find the problem after purchase. Threshold segmentation method is a region-based image segmentation techniques, whose basic principle is: by setting a different characteristic threshold, the image pixel is divided into several categories. The common features include: directly from the original image grayscale or color characteristics; characteristics of transformation obtained by the original grayscale or color values. The set of the original image f (x, Y,), according to certain criteria, ie, commonly referred to as image binarization.
Image Thresholding this seemingly simple question, from a wide range of domestic and foreign scholars in the past four decades, resulting in hundreds of threshold selection method, but unfortunately, like other image segmentation algorithm, an existing method for a variety of images can get satisfactory results, nor even a theory to guide us to choose a particular method to deal with specific images. The merchants often base on the testing and did not accept the complaint of the consumers about the cufflinks.