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Breast cancer is one of the most common cancers worldwide. Breast cancer rates are high in low- and middle-income countries, where breast tumors are diagnosed late. Early detection of masses or abnormalities that indicate breast cancer is a very important step for treating breast cancer in its first stages. The early detection of breast cancer tumors depends on both the ability of radiologists to...
Breast cancer is one from various diseases that has got great attention in the last decades. This due to the number of women who died because of this disease. Segmentation is always an important step in developing a CAD system. This paper proposed an automatic segmentation method for the Region of Interest (ROI) from breast thermograms. This method is based on the data acquisition protocol parameter...
In recent years, shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are limited to finding and resolving one object overlap per scene and require user intervention for model initialization. In this paper, we present a novel synergistic segmentation scheme called Active Contour for Overlap Resolution using Watershed (ACOReW)...
This paper presents a smart and simple algorithm for vehicle's license plate recognition system. The proposed algorithm consists of three major parts namely detection of license plate from an image, segmentation and recognition of characters. For detection of the license plate, a memory and speed proficient algorithm has been proposed. After detection, statistical based template matching is used for...
This paper presents a new approach of anisotropic diffusion to classify the weed images into broad and narrow class for real time selective herbicide application. The classifier we proposed based on Perona and Malik equation. Its low computational complexity and fast runtimes makes this method well suited for real-time vision applications. The developed system has been tested on weeds in the lab;...
This paper proposes a framework in which Lagrangian particle dynamics is used for the segmentation of high density crowd flows and detection of flow instabilities. For this purpose, a flow field generated by a moving crowd is treated as an aperiodic dynamical system. A grid of particles is overlaid on the flow field, and is advected using a numerical integration scheme. The evolution of particles...
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