Automated Focal Liver Lesion Staging Classification based on Haralick Texture Features and Multi-SVM
نویسندگان
چکیده
منابع مشابه
Fast Calculation of Haralick Texture Features
It is our aim in this research to optimize the numerical computation of the Haralick texture features [1] that consists of two steps. Haralick texture features are used as a primary component to discern between different protein structures in microscopic bio-images. The first of these two parts is the construction of the co-occurrence matrix. Upon completion of this implementation, we will atte...
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Retrieval of an image is a more effective and efficient for managing extensive image database. Content Based Image Retrieval (CBIR) is a one of the image retrieval technique which uses user visual features of an image such as color, shape, and texture features etc. It permits the end user to give a query image in order to retrieve the stored images in database according to their similarity to t...
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According to recent researches, glaucoma, an optic nerve disease, is considered as one of the major causes which can lead to blindness. It has affected a huge number of people worldwide. Rise in intraocular pressure of the eye leads to the disease resulting in progressive and permanent visual loss. Texture of normal retinal image and glaucoma image is different. Here texture property of the tot...
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The classification of remotely sensed images knows a large progress taking in consideration the availability of images with different resolutions as well as the abundance of classification’s algorithms. A number of works have shown promising results by the fusion of spatial and spectral information using Support vector machines (SVM) which are a group of supervised classification algorithms tha...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2014
ISSN: 0975-8887
DOI: 10.5120/15901-4953