Unsupervised texture segmentation using Gabor filters
Anil K. Jain,Farshid Farrokhnia +1 more
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TLDR
A texture segmentation algorithm inspired by the multi-channel filtering theory for visual information processing in the early stages of human visual system is presented, which is based on reconstruction of the input image from the filtered images.About:
This article is published in Pattern Recognition.The article was published on 1991-12-01 and is currently open access. It has received 2351 citations till now. The article focuses on the topics: Image texture & Texture filtering.read more
Citations
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Journal ArticleDOI
A discrete region competition approach incorporating weak edge enhancement for ultrasound image segmentation
TL;DR: To prevent regions from leaking out of the desired area across weak edges, edges located on the slowly varying slope are enhanced according to their position on the slope and the length of the slope.
Journal ArticleDOI
Iris Segmentation in Visible Wavelength Images using Circular Gabor Filters and Optimization
TL;DR: A new iris segmentation method based on the Circular Gabor Filter and optimization and robust to reflections is proposed, which reveals the effectiveness of the proposed method in comparison with some of state-of-the-art methods.
Proceedings ArticleDOI
Document image segmentation using Gabor wavelet and kernel-based methods
TL;DR: Kernel-based methods and Gabor wavelet are applied to the document image segmentation and the initial segmentation is obtained by assigning class labels to pixels of the feature image with the trained SVM.
Proceedings ArticleDOI
An improved font recognition method based on texture analysis
TL;DR: Experimental results show that RR can be improved and the adjustments are useful, and several dictionaries are set to deal with the diversity in textures of the same font.
Proceedings ArticleDOI
An integrated color and texture feature based framework for content based image retrieval using 2D Wavelet Transform
V. Balamurugan,P. Anandhakumar +1 more
TL;DR: An integrated color and texture feature based content based image retrieval using 2D Discrete Wavelet Transform (2D-DWT) to provide efficient in terms of retrieval accuracy and precision.
References
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Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
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Statistical and structural approaches to texture
TL;DR: This survey reviews the image processing literature on the various approaches and models investigators have used for texture, including statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models.
Journal ArticleDOI
Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters.
TL;DR: Evidence is presented that the 2D receptive-field profiles of simple cells in mammalian visual cortex are well described by members of this optimal 2D filter family, and thus such visual neurons could be said to optimize the general uncertainty relations for joint 2D-spatial-2D-spectral information resolution.