Handwriting differs from person to person. Some may be legible while some others are difficult to read or understand. Hence this project aims at recognizing the handwritten text and understanding what it is with the help of a neural network and fuzzy logic. It involves segmentation, feature extraction and classification.Here the method used is Canny Edge Detection Algorithm and the Histogram Of...

A fuzzy graph can be obtained from two given fuzzy graphs using union and join. In this paper, we find the degree of an edge in fuzzy graphs formed by these operations in terms of the degree of edges in the given fuzzy graphs in some particular cases. 1. Introduction Fuzzy graph theory was introduced by Azriel Rosenfeld in 1975 [4]. Though it is very young, it has been growing fast and has nume...

In this work the method of masks, creating and using of inverted image masks, together with binary operation of image data are used in edge detection of binary images, monochrome images, which yields about 300 times faster than ordinary methods. The method is divided into three stages: Mask construction, Fundamental edge detection, and Edge Construction Comparison with an ordinary method and a ...

Crack evaluation is essential for effective classification of pavement cracks. Digital images of pavement cracks have been analyzed using techniques such as fuzzy set theory and neural networks. Bidimensional empirical mode decomposition (BEMD), a new image analysis method recently developed, can potentially be used for pavement crack evaluation. BEMD is an extension of the empirical mode decom...

background: breast cancer is currently one of the leading causes of death among women worldwide. the diagnosis and separation of cancerous tumors in mammographic images require accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. objective: this paper proposes a new algorithm which draws on discrete wavelet transform and adaptive...

image recognition is one of the most important field in image processing that in recent decades had much attention .due to expansion of related fields with image processing and various application of this science in machine vision, military science, geography, aerospace and artificial intelligence and lots of other aspects, out stand the importance of this subject.one of the most important aspe...

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we cons...

in order to obtain maximum information from magnetic and gravity anomaly maps, application of an edgedetection method is necessary. in this regard two commonly used methods are derivative filters and local phase filters. in this paper, a matlab code is expanded to combine an analytic signal filter and a tilt angle filter as a new edge detection filter called asta filter. this method was demonst...

This paper describes edge detection as a composition of four steps: conditioning, feature extraction, blending, and scaling. We examine the role of geometry in determining good features for edge detection and in setting parameters for functions to blend the features. We find that: 1) statistical features such as the range and standard deviation of window intensities can be as effective as more ...

In this paper, the minimum spanning tree problem is investigated on the graph with fuzzy edge weights. The notion of fuzzy α-minimum spanning tree is presented based on the credibility measure, and then the solutions of the fuzzy α-minimum spanning tree problem are discussed under different assumptions. First, we respectively assume that all the edge weights are triangular fuzzy numbers and tra...