Tlreshold Selection Method from Gray-Level Histograms
نویسنده
چکیده
A nonparametric and unsupervised method ofautomatic threshold selection for picture segmentation is presented. An optimal threshold is selected by the discriminant criterion, namely, so as to maximize the separability of the resultant classes in gray levels. The procedure is very simple, utilizing only the zerothand the first-order cumulative moments of the gray-level histogram. It is straightforward to extend the method to multithreshold problems. Several experimental results are also presented to support the validity of the method.
منابع مشابه
Analysis Tools for Gray Level Histograms
This paper summarizes three algorithms used for the analysis of gray level histograms. Two of them are easily developed from standard techniques and the other is a completely new method. We will study the advantages of each and give examples of real-world use. Gray level histogram analysis (mainly threshold computation) is a known technique that allows easy and fast segmentation of the regions ...
متن کاملModified Dynamic Histogram Equalization For Image Enhancement in Gray-scale Images
To improve the quality of digital images captured in low light environment from consumer electronics devices like cell phone cameras, Modified Dynamic Histogram Equalization (MDHE) is proposed. Initially, the proposed method divides the histogram into two sub-histograms based on median. Then 2 subhistogram is further divided into two sub-histograms based on median of it. The resultant sub-histo...
متن کاملA new image thresholding method based on Gaussian mixture model
Abstract: In this paper, an efficient approach to search for the global threshold of image using Gaussian mixture model is proposed. Firstly, a gray-level histogram of an image is represented as a function of the frequencies of gray-level. Then,to fit the Gaussian mixtures to the histogram of image, the Expectation Maximization (EM) algorithm is developed to estimate the number of Gaussian mixt...
متن کاملImage Bi-Level Thresholding Based on Gray Level-Local Variance Histogram
Thresholding is a popular method of image segmentation. Many thresholding methods utilize only the gray level information of pixels in the image, which may lead to poor segmentation performance because the spatial correlation information between pixels is ignored. To improve the performance of thresolding methods, a novel two-dimensional histogram—called gray level-local variance (GLLV) histogr...
متن کاملGray level cooccurrence histograms via learning vector quantization
In this paper, we propose to use learning vector quantization for the efficient partitioning of a cooccurrence space. A simple codebook is trained to map the multidimensional cooccurrence space into a 1-dimensional cooccurrence histogram. In the classification phase a nonparametric log-likelihood statistic is employed for comparing sample and prototype histograms. The advantages of vector quant...
متن کامل