Optical–digital processing of directional terrain textures invariant under translation, rotation, and change of scale

Duvernoy, J.

doi:10.1364/ao.23.000828

Cited by 46 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Duvernoy [16] uses the technique of Fourier descriptors to extract the invariant texture signature on the spectrum domain of the original texture. In his method, the image is characterized by the optical Fourier spectrum of the texture.…”

Section: Optical Digital Methodsmentioning

confidence: 99%

Brief review of invariant texture analysis methods

Zhang¹,

Tan

2002

Pattern Recognition

384

171

View full text Add to dashboard Cite

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. ?

show abstract

Section: Optical Digital Methodsmentioning

confidence: 99%

Brief review of invariant texture analysis methods

Zhang¹,

Tan

2002

Pattern Recognition

384

171

View full text Add to dashboard Cite

show abstract

“…Davis [10] exploited polarograms and generalized co-occurrence matrices to obtain rotation invariant statistical features. In [11], Duvernoy proposed Fourier based descriptors to extract texture feature on the frequency domain. In [12] Eichmann and Kasparis presented texture descriptors based on line structures extracted by the Hough transform.…”

Section: Related Workmentioning

confidence: 99%

Photographic paper texture classification using model deviation of local visual descriptors

Picard¹,

Vu²,

Fijalkow³

2014

2014 IEEE International Conference on Image Processing (ICIP)

View full text Add to dashboard Cite

This paper investigates the classification of photographic paper textures using visual descriptors. Such classification is called fine grain due to the very low inter-class variability. We propose a novel image representation for photographic paper texture categorization, relying on the incorporation of a powerful local descriptor into an efficient higher-order model deviation where texture is represented by computing statistics on the occurrences of specific local visual patterns. We perform an evaluation on two different challenging datasets of photographic paper textures and show such advanced methods indeed outperforms existing descriptors.

show abstract

“…Extract contour signature using Fourier slice analysis 3. Extract affine invariant features from the signature using Fourier description An analogous approach [4] was suggested in 80s, which was developed for remote sensing of terrains but different in the contour definition.…”

Section: Affine Invariant Featuresmentioning

confidence: 99%

“…A simple division of both sides by either side produces an absolute affine invariant feature. For more details, readers are referred to [4].…”

Section: Extraction Of Affine Invariant Featurementioning

confidence: 99%

Structural Texture Segmentation using Affine Symmetry

Park

Martin

Bhalerao

2007

2007 IEEE International Conference on Image Processing

View full text Add to dashboard Cite

Many natural textures comprise structural patterns and show strong self-similarity. We use affine symmetry to segment an image into self-similar regions; that is a patch of texture (blocks from a uniformly partitioned image) can be transformed to other similar patches by warping. If the texture image contains multiple regions, we then cluster patches into a number of classes such that the overall warping error is minimized. Discovering the optimal clusters is not trivial and known methods are computationally intensive due to the affine transformation. We demonstrate efficient segmentation of structural textures without affine computation. The algorithm uses Fourier Slice Analysis to obtain a spectral contour signature. Experimental evaluation on structural textures shows encouraging results and application on natural images demonstrates identification of texture objects.

show abstract

Optical–digital processing of directional terrain textures invariant under translation, rotation, and change of scale

Cited by 46 publications

References 22 publications

Brief review of invariant texture analysis methods

Brief review of invariant texture analysis methods

Photographic paper texture classification using model deviation of local visual descriptors

Structural Texture Segmentation using Affine Symmetry

Contact Info

Product

Resources

About