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Malignant melanomas are the most serious form of skin cancer accounting for the majority of skin cancer related deaths. Histo-pathological images of skin tissues are analyzed for detecting various types of melanomas. The automatic analysis of these images can greatly facilitate the diagnosis task for dermato-pathologists. The first and foremost step in automatic histo-pathological image analysis is...
This paper presents Improved Mountain Clustering (IMC) based medical image segmentation. Proposed technique is a more powerful approach for X-Ray image based diagnosing diseases like lung cancer and tuberculosis. The IMC based segmentation approach was applied on lung X-Ray images and compared with some existing techniques such as K-Means and FCM based segmentation approaches. The performance of all...
Localization of edges and corner points by fuzzy detectors in images is the main concern of this paper. This paper presents an approach to edge and corner detection based on fuzzy logic. In this approach SUSAN mask is employed to compute USAN area. The histogram of USAN area permits us construct type 1 and type 2 fuzzy membership functions by fuzzifying USAN area computed about every pixel in an image...
In this paper, palmprint based authentication is presented. The palmprint image is acquired using an acquisition system developed at IIT Delhi. The region of interest (ROI) is extracted from the palmprint image by finding a tangent of curves between fingers. The perpendicular bisector of this tangent divides the rectangular area enclosing the palmprint into two equal parts. The features extracted...
Mammography is considered as the most effective means for breast cancer diagnosis. This paper introduces two separate techniques for mass and micro-calcification segmentation in digital mammograms. Segmentation of masses consists of three steps- background subtraction, fuzzy texture representation and entropic thresholding. Similarly micro-calcifications are also segmented in three stages - background...
This paper proposes a fuzzy logic based edge detector for feature extraction in biometric systems such as face and palm print recognition. Edge detection is carried out by means of global (histogram of gray levels) and local (pixels within in a window) information. The local information is fuzzified by employing a modified Gaussian membership function. Using the contrast intensification operator,...
This paper presents the recognition of handwritten Hindi numerals based on the modified exponential membership function fitted to the fuzzy sets derived from normalized distance features obtained using the box approach. The exponential membership function is modified by two structural parameters that are estimated by optimizing the criterion function associated with the input fuzzy modeling. We then...
This paper presents a novel approach for edge detection based on the univalue segment assimilating nucleus (USAN) area. The USAN area characterizes the structure of the edge present in the neighborhood of a pixel and can thus be considered as a unique feature of the pixel and is fuzzified. The Gaussian edge detector mask is then applied to the associated Gaussian membership function of the USAN area...
This paper presents Gaussian and impulse noise filters for eliminating mixed noise in images. For Gaussian filter, the fuzzy set called "small" is derived to represent the disorder in a pixel arising out of neighborhood corrupted with Gaussian. The expression for correction is developed based on the intensity of the central pixel and the membership function. Similarly, the correction for...
The cluster-weighted modeling (CWM) is a mixture density estimator around local models. To be specific, the input regions together with output regions are treated to be Gaussian serving as local models. These models are linked by a linear function involving the mixture of densities of local models. A connection between the CWM and generalized fuzzy model (GFM) is established in this work for utilizing...
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