Results 261 to 270 of about 32,666,734 (297)

Image Texture Analysis - Survey

2013 Third International Conference on Advanced Computing and Communication Technologies (ACCT), 2013
This paper discusses the various methods used to analyze the texture property of an image. Texture analysis is broadly classified into three categories: Pixel based, local feature based and Region based. Pixel based method uses grey level co occurrence matrices, difference histogram and energy measures and Local Binary Patterns(LBP) Local feature based
A. Dixit, N. P. Hegde
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Texture analysis assessment for images

2016 8th International Conference on Information Technology and Electrical Engineering (ICITEE), 2016
Commonly, the existing metrics such as mean square error (MSE), peak signal-to-noise ratio (PSNR), quality index (QI), structural similarity index metric (SSIM), and quality index based on local variance (QILV) use the image intensity-based statistics approach to assess the quality of distorted images. These metrics are successful in discriminating the
Taravichet Titijaroonroj, Yothin Kaewaramsri, Ungsumalee Suttapakti, Kuntpong Woraratpanya, Yoshimitsu Kuroki   +4 more
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Texture analysis of CT images

IEEE Engineering in Medicine and Biology Magazine, 1995
The present study has shown some promise in the use of texture for the extraction of diagnostic information from CT images. A number of features are obtained from abdominal CT scans of the liver using the spatial domain statistical texture analysis methods: SGLDM, GLRLM, and GLDM.
A.H. Mir, M. Hanmandlu, S.N. Tandon
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Texture analysis of SAR images

1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications, 2002
Texture features derived from the grey level co-occurrence matrix (GLCM) and the fractal dimension were evaluated for a SAR image. The local values of the texture features for every pixel in the image were evaluated in a small (16 by 16 pixels) window around each pixel.
null Soo Chin Liew, null Hock Lim, null Leong Keong Kwoh, null Geok Kee Tay   +3 more
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Image-based texture analysis for realistic image synthesis

Proceedings 13th Brazilian Symposium on Computer Graphics and Image Processing (Cat. No.PR00878), 2002
We present a method to measure reflectance and texture of surfaces in a one step process. For later use in digital image synthesis, it is mandatory to separate the gathered intensity values into these two parts to eliminate highlighting artifacts from textures. Our image based measurement system delivers bidirectional reflectance distribution function (
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TEXTURE ANALYSIS IN MEDICAL IMAGING

1997
The main objective of any diagnostic study of image is the characterization of tissues. Therefore images are acquired in order to determine whether the tissues in the selected area for study show normal (healthy tissue) or pathological characteristics.
Bruno Alain, Collorec René, Bézy-Wendling Johanne, Reuzé Patrick, Rolland Yann   +4 more
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Texture analysis of parasitological liver fibrosis images

Microscopy Research and Technique, 2017
AbstractLiver fibrosis accurate staging is vital to define the state of the Schistosomiasis disease for further treatment. The present work analyzed the microscopic liver images to identify and to differentiate between healthy, cellular, fibrocellular, and fibrous liver pathologies by proposing a fast, robust, and highly discriminative method based on ...
Luminiţa Moraru, Simona Moldovanu, Anisia‐Luiza Culea‐Florescu, Dorin Bibicu, Amira S. Ashour, Nilanjan Dey   +5 more
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Counterfeit IC Detection By Image Texture Analysis

2017 Euromicro Conference on Digital System Design (DSD), 2017
The widespread penetration of counterfeit integrated circuits (ICs) is not only a major threat to the electronic goods supply chain, but also constitute a great threat to national security. Image processing based counterfeit IC design techniques are promising, but currently often suffer from high computational complexity and requirement of expensive ...
Pallabi Ghosh, Rajat Subhra Chakraborty
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Image analysis and compression: renewed focus on texture

SPIE Proceedings, 2010
We argue that a key to further advances in the fields of image analysis and compression is a better understanding of texture. We review a number of applications that critically depend on texture analysis, including image and video compression, content-based retrieval, visual to tactile image conversion, and multimodal interfaces.
Thrasyvoulos N. Pappas, Jana Zujovic, David L. Neuhoff   +2 more
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Computerised texture image analysis of biocrystallisation images

2006
Elemente der Naturwissenschaft 85, p. 111-111.
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