Texture analysis Anno 1983

Gool, Luc Van; Dewaele, Piet; Oosterlinck, André

doi:10.1016/0734-189x(85)90130-6

Cited by 339 publications

(42 citation statements)

References 60 publications

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“…Many authors have developed those statistical properties for invariant texture analysis. In the early 1980s about the time Davis did the polarogram work, some e orts on texture analysis were made to achieve texture invariance [5,8]. In the following subsections, we will address the existing invariant texture methods based on statistics.…”

Section: Methodsmentioning

confidence: 99%

“…Surveys of existing texture analysis approaches may be found in Refs. [1][2][3][4][5][6][7][8]. Comparative studies of a subset of texture analysis methods can also be found in Refs.…”

Section: Introductionmentioning

confidence: 99%

“…Existing texture analysis methods are broadly divided into two categories: statistical methods and structural methods in most of the surveys [1][2][3][4][5][6][7][8]. But in the recent literature, many model based methods have been employed in texture analysis [10], including autoregressive model, Gausian Markov random ÿelds, Gibbs random ÿelds, Wold model, wavelet model, multichannel Gabor model and steerable pyramid, etc.…”

Section: Introductionmentioning

confidence: 99%

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Brief review of invariant texture analysis methods

Zhang¹,

Tan

2002

Pattern Recognition

386

171

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This paper considers invariant texture analysis. Texture analysis approaches whose performances are not a ected by translation, rotation, a ne, and perspective transform are addressed. Existing invariant texture analysis algorithms are carefully studied and classiÿed into three categories: statistical methods, model based methods, and structural methods. The importance of invariant texture analysis is presented ÿrst. Each approach is reviewed according to its classiÿcation, and its merits and drawbacks are outlined. The focus of possible future work is also suggested. ?

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Section: Methodsmentioning

confidence: 99%

“…Surveys of existing texture analysis approaches may be found in Refs. [1][2][3][4][5][6][7][8]. Comparative studies of a subset of texture analysis methods can also be found in Refs.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Brief review of invariant texture analysis methods

Zhang¹,

Tan

2002

Pattern Recognition

386

171

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“…Texture analysis methods have been reviewed in several papers [100,87,204,119]. This section focuses on filter bank methods and co-occurrence matrices.…”

Section: Previous Work On Texture Classificationmentioning

confidence: 99%

“…Texture analysis is an active research field and a large number of schemes for texture feature extraction have been proposed [100,87,204]. We have developed a texture feature extraction method based on a scale-space description of local histograms (see Chapter 5).…”

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confidence: 99%

Computer aided diagnosis in chest radiography

Mouton¹,

Douglas

2003

Academic Radiology

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Analysis of skin images using texture descriptor by a combined statistical and structural approach

Umarani¹,

Ganesan²,

Sudhakar

2007

Int J Imaging Syst Tech

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In this article, an attempt has been made to analyze various skin (textured) images. They are caused because of hot water, chemical, electrical, thermal, cigarette, etc. These images are analyzed using our texture representation scheme. Our approach uses a set of 92 texture primitives. They are tested for the presence of texture by a statistical design of experiments based approach [Ganesan and Bhattacharyya, Pattern Recogn 28 (1995), 99-105]. These texture primitives are concluded as the local descriptor and their distribution over the entire image is the global representation called texture primitive spectrum. The set of texture primitives and the texture primitive spectrums are successful for a number of Bench mark images (Brodatz, Texture-A photographic album for artists and designers, Reinbold, New York, 1968; Vistex, Available at http://www.white.media. mit.edu\vismod\imgery\Vision Texture, MIT Media Lab, 1995). Using the texture primitive spectrum, several texture images have been categorized as micro, macro, fine, and coarse and a trend is obtained. Similarly, a set of skin images affected by severe burn with many causes are analyzed. The severity has been quantified and concluded based on simple and weighted mean computed for the texture primitive spectrums. The extent of burn and hence the curing duration can be approximated from the results. The outcome of our experimentation with ground truth and the opinion from the experts are closely matching.

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Texture analysis Anno 1983

Cited by 339 publications

References 60 publications

Brief review of invariant texture analysis methods

Brief review of invariant texture analysis methods

Computer aided diagnosis in chest radiography

Analysis of skin images using texture descriptor by a combined statistical and structural approach

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