Results 171 to 180 of about 102,250 (219)

Textural analysis of range images

Pattern Recognition Letters, 1991
Abstract This paper addresses the problem of texture discrimination in range images. The range data is transformed to a common coordinate system, and then resampled to generate a regular grid of points in order to eliminate the effect of different sampling rates.
Arya, Sunil, DeMenthon, D., Meer, P., Davis, L.S.   +3 more
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Unsupervised textured image segmentation

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992
A new algorithm for unsupervised textured image segmentation is presented. The image comprises M textured regions, each of which is modeled by a stationary Gaussian Markov random field. A feature vector is computed for each pixel in the original image where these vectors are normally distributed and cluster about some vector means. Thus, the problem is
George K. Gregoriou, Oleh J. Tretiak
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Textures for realistic image synthesis

Computers & Graphics, 1985
Abstract An important aspect in generating images of real materials and surfaces is the contribution of the visual effects of textures. This study presents methods for simulating a variety of different textures. Two general types of texture, geometric and spectral, are simulated. Geometric textures incorporate the irregularities and variations which
Richard J. Carey, Donald P. Greenberg
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COMPUTING IMAGE TEXTURE BY ISOPATTERN

International Journal of Pattern Recognition and Artificial Intelligence, 2014
Texture is an important feature that aids in identifying objects of interest or region of interest irrespective of the source of the image. In this paper, a novel and simple isopattern-based texture feature is introduced. Spatial gray scale dependencies represented by bit plane is analyzed for specific patterns and are accumulated in bins.
S. Mohamed Mansoor Roomi, R. Raja, D. Kalaiyarasi   +2 more
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Textural Features for Image Classification

IEEE Transactions on Systems, Man, and Cybernetics, 1973
Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes some easily computable textural features based on gray-tone spatial dependancies, and illustrates their application in category ...
Robert M. Haralick, Karthikeyan S. Shanmugam, Its'hak Dinstein   +2 more
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Texture Features and Image Texture Models

2019
Image texture is an important phenomenon in many applications of pattern recognition and computer vision. Hence, several models for deriving texture properties have been proposed and developed. Although there is no formal definition of image texture in the literature, image texture is usually considered the spatial arrangement of grayscale pixels in a ...
Chih-Cheng Hung, Enmin Song, Yihua Lan
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On indexing the periodicity of image textures

Image and Vision Computing, 2001
Abstract Texture analysis is an important part in many computer vision tasks, and periodicity (regularity) is one of the most important texture features. Based on the structural view of texture, we describe a new way to index the periodicity of image textures in this paper.
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Permutational model of image texture

Signal Processing: Image Communication, 1995
Very often computer simulation is practically the only method of image processing studies. To organize a simulation experiment one ought to have efficient simulation algorithms of random image components. Textures form a very important class of such components.
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Unsupervised segmentation of textured images

Information Sciences, 1996
Abstract In this paper, a new unsupervised segmentation algorithm for textured images is developed. The proposed algorithm utilizes the characteristic of the Markov random fields (MRF) for modeling the contextual information embedded in image formation.
Jaehyun Park, Ludwik Kurz
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Browsing Texture Image Databases

11th International Multimedia Modelling Conference, 2005
The MPEG-7 standard defines two types of texture features: texture retrieval descriptor (TRD) for retrieval and texture browsing descriptor (TBD)for browsing. The retrieval process is straightforward but it is unclear how one could use TBD for browsing. This paper describes two methods of generating layouts for browsing a texture image database.
Suryani Lim, Lianping Chen, Guojun Lu, Ray Smith   +3 more
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