Image thresholding based on Ali-Silvey distance measures
نویسندگان
چکیده
-A relative entropy based approach to image thresholding was proposed recently. It was demonstrated that this method was successful for image thresholding. Relative entropy is a member of the class of Ali-Silvey distance measures. In this paper we generalize the relative entropy based approach and present image thresholding algorithms based on the class of Ali-Silvey distance measures. A number of members of this class are selected and used for implementation in image thresholding algorithms. Performance is evaluated by applying these algorithms to several images and comparing them to a few histogram based thresholding methods. © 1997 Pattern Recognition Society. Published by Elsevier Science Ltd. Thresholding Relative entropy Image processing Segmentation Co-occurrence matrix Ali-Silvey distance measures
منابع مشابه
Robust Potato Color Image Segmentation using Adaptive Fuzzy Inference System
Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...
متن کاملVariational non rigid image registration using exclusive F-information
We address the problem of robust non rigid image registration and focus our interest on similarity criteria based on generalized information measures within the Ali-Silvey class. We introduce exclusive -information as a novel class of similarity functionals, and develop a generic variational framework for their optimization over non-parametric and parametric transform spaces. This approach is a...
متن کاملSome inequalities for information divergence and related measures of discrimination
Inequalities which connect information divergence with other measures of discrimination or distance between probability distributions are used in information theory and its applications to mathematical statistics, ergodic theory and other scientific fields. We suggest new inequalities of this type, often based on underlying identities. As a consequence we obtain certain improvements of the well...
متن کاملBlock-Based Compressive Sensing Using Soft Thresholding of Adaptive Transform Coefficients
Compressive sampling (CS) is a new technique for simultaneous sampling and compression of signals in which the sampling rate can be very small under certain conditions. Due to the limited number of samples, image reconstruction based on CS samples is a challenging task. Most of the existing CS image reconstruction methods have a high computational complexity as they are applied on the entire im...
متن کاملA comparative performance of gray level image thresholding using normalized graph cut based standard S membership function
In this research paper, we use a normalized graph cut measure as a thresholding principle to separate an object from the background based on the standard S membership function. The implementation of the proposed algorithm known as fuzzy normalized graph cut method. This proposed algorithm compared with the fuzzy entropy method [25], Kittler [11], Rosin [21], Sauvola [23] and Wolf [33] method. M...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Pattern Recognition
دوره 30 شماره
صفحات -
تاریخ انتشار 1997