نتایج جستجو برای: ماتریس glcm
تعداد نتایج: 10060 فیلتر نتایج به سال:
شناسایی حروف نوشتاری و نوری نقش مهمی در کاربردهای جدیدی مثل پزشکی و حمل و نقل و سیستم های امنیتی دارد. تاکنون سیستم های شناسایی حروف مختلفی ارائه شده است که هرکدام در یک زمینه کاربردی بکار می روند.در این پایان نامه یک روش جدی برای شناسایی حروف انگلیسی بر مبنای ماتریس gray level co-occurrence matrix (glcm) ارائه شده است.ماتریس glcm بطور وسیعی در کاربرد دسته بندی بافت استفاده می شود. بعد از یک سر...
به منظور نظارت بر نحوه گسترش شهر و تغییرات بر محیط زیست، طبقه بندی پوشش زمین یک چالش و همچنین کار ضروری است. در این پروژه روشی ترکیبی جهت بخش بندی و طبقه بندی تصاویر sar نواحی شهری ارائه شده است.برای طبقه بندی این تصاویر، طبقه بندی کننده های knn و svm به کار گرفته شده اند.در روش پیشنهادی، دو دسته ویژگی های نوع اول و ویژگی های نوع دوم برای آموزش طبقه بندی کننده در نظر گرفته شده اند. برای محاسبه ...
In this paper, a new face recognition technique is introduced based on the gray-level co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the information about relative positions of neighboring pixels of an image. We proposed two methods to extract feature vectors using GLCM for face classification. The first method extracts the well-known Haralick features fro...
Abstract— Dental radiographs are essential in diagnosing the pathology of the jaw. However, similar radiographic appearance of jaw lesions causes difficulties in differentiating cyst from tumor. Therefore, we conducted a development of computer-aided classification system for cyst and tumor lesions in dental panoramic images. The proposed system consists of feature extraction based on texture u...
Early detection of medical renal disease is important as the same may lead to chronic kidney disease which is an irreversible stage. The present work proposes an efficient decision support system for detection of medical renal disease using small feature space consisting of only second order GLCM statistical features computed from raw renal ultrasound images. The GLCM mean feature vector and GL...
The grey level co-occurrence matrix (GLCM) is used in this work for quantitative spatial texture description. The two GLCM metrics, offset and contrast, are used to quantify spatial intensity variation. It is shown that the optimal DIC pattern must possess low critical GLCM offset and high nominal GLCM contrast. A very strong correlation between the critical GLCM contrast and the correlation wi...
This study extended the computation of GLCM (gray level co-occurrence matrix) to a three-dimensional form. The objective was to treat hyperspectral image cubes as volumetric data sets and use the developed 3D GLCM computation algorithm to extract discriminant volumetric texture features for classification. As the kernel size of the moving box is the most important factor for the computation of ...
Collagen is the most prominent protein in the human body, making up 30% of the total protein content. Quantitative studies have shown structural differences between collagen fibers of the normal and diseased tissues, due to the remodeling of the extracellular matrix during the pathological process. The dominant orientation, which is an important characteristic of collagen fibers, has not been t...
In this study, an efficient feature fusion based technique for the classification of colour texture images in VisTex album is presented. Gray Level Co-occurrence Matrix (GLCM) and its associated texture features contrast, correlation, energy and homogeneity are used in the proposed approach. The proposed GLCM texture features are obtained from the original colour texture as well as the first no...
This article presents a hybrid approach for texture-based image classification using the gray-level co-occurrence matrices (GLCM) and a new Fuzzy Kohonen Clustering Network for Symbolic Interval Data (IFKCN). The GLCM matrices extracted from an image database are processed to create the training data set using IFKCN algorithm. The IFKCN organizes and extracts prototypes from processed GLCM matr...
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