Automatic Histogram Threshold with Fuzzy Measures using C-means
نویسندگان
چکیده
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems involved in finding the minimum of a criterion function are avoided. Similarity between gray levels is the key to find an optimal threshold. Two initial regions of gray levels, located at the boundaries of the histogram, are defined. Then, using an index of fuzziness, a similarity process is started to find the threshold point. A significant contrast between objects and background is assumed. Previous histogram equalization is used in small contrast images. Fuzzy c-means (FCM) is a method of clustering which allows one piece of data to belong to two or more clusters. This method is frequently used in pattern recognition. It is based on minimization of the objective function ! No prior knowledge of the image is required.
منابع مشابه
Knowledge Based Brain Tumor Segmentation using Local Maxima and Local Minima
In this work, we have a proposed an automatic method to brain tumor segmentation using magnetic resonance imaging (MRI) histogram. In our proposed method input is taken from abnormal slice of the MRI volume. Based on image histogram of the abnormal slice, our algorithm automatically detected the local minima and maxima using histogram smoothing techniques. Threshold value obtained from local mi...
متن کاملFingerprint: DWT, SVD Based Enhancement and Significant Contrast for Ridges and Valleys Using Fuzzy Measures
The performance of the Fingerprint recognition system will be more accurate with respect of enhancement for the fingerprint images. In this paper we develop a novel method for Fingerprint image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition (SVD) has been proposed. This technique is compared with conventional image equalization tech...
متن کاملAutomatic Image Segmentation using Ultra Fuzziness
In this paper, an automatic histogram threshold approach based on a fuzzy measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems involved in finding the minimum/maximum of a entropy criterion function are avoided. Hamid R Tizhoosh defined a membership function to measure the image fuzziness, which makes the methodology totally supervise...
متن کاملHybrid Image Segmentation using Discerner Cluster in FCM and Histogram Thresholding
Image thresholding has played an important role in image segmentation. This paper presents a hybrid approach for image segmentation based on the thresholding by fuzzy c-means (THFCM) algorithm for image segmentation. The goal of the proposed approach is to find a discerner cluster able to find an automatic threshold. The algorithm is formulated by applying the standard FCM clustering algorithm ...
متن کاملA Comparative Study on Image Segmentation Based on Artificial Bee Colony Optimization and FCM
The goal of image segmentation is to cluster the pixels of an image into several regions. This article describes the method of image segmentation using Artificial Bee Colony Optimization (ABC). This optimization technique is motivated by intelligent behaviour of honey bees and it provides a population based search procedure. In this article Gaussian Mixture Model (GMM) is used and each pixel cl...
متن کامل