Image database indexing and retrieval using the Fractal Transform

Marie-Julie, Jean Michel; Essafi, Hassane

doi:10.1007/bfb0037351

Cited by 11 publications

(11 citation statements)

References 12 publications

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“…Fractal feature extractors have been shown before to be effective for indexing multimedia database consisting of texture images [3,8,9,10]. In [9] we demonstrated the invariance of the features, including those from Section 3.2 for rotation, translation, folding and brightness adjustments.…”

Section: Experiments Results and Discussionmentioning

confidence: 72%

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Image databases, scale and fractal transforms

Schouten¹,

Zeeuw²

2000

Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)

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In contemporary image databases one finds many images with the same image content but perturbed by zooming, scaling, rotation etc. For the purpose of image recognition in such databases we employ features based on statistics stemming from fractal transforms of gray-scale images. We show how the features derived from these statistical aspects can be made invariant to zooming or rescaling. A feature invariance measure is defined and described. The method is especially suitable for images of textures. We produce numerical results which validate the approach.

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Section: Experiments Results and Discussionmentioning

confidence: 72%

“…Such a relationship can be used to create fractal features, invariant under scaling. The paper is concerned with the use of fractal transformations as feature extractors [1,2,3,4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Image databases, scale and fractal transforms

Schouten¹,

Zeeuw²

2000

Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)

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“…They convert texture and edge of pattern into fractal code and then use it for searching process. [5] In 1998, in his PhD thesis, Shih used fractal compression technique to search specific gamma images from nucleus dataset. In addition, he found that a-priori knowledge of the data can help the computer to recognize images more efficient.…”

Section: Literature Reviewmentioning

confidence: 99%

The Application of Fractal Concept to Content-Based Image Retrieval

Shih¹

2010

Application of Machine Learning

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“…Each function out of the system acts, by contrast scaling and luminance offset on the gray values of a local area of the image. This paper is concerned with the use of fractal transformations as feature extractors [1,6,7,8,11,12]. One of the reasons we want to investigate this problem is that many databases suffer from duplications.…”

Section: Pifs Part Of Image Part Of Image Numerousmentioning

confidence: 99%

“…Most of the fractal feature extractors use the parameters, discussed in the previous section, to describe the image or object [1,7,9]. Kouzani et al [6] uses only the e x f x parameters; Baldoni et al [1] and Vissac et al [12] use simplified or altered fractal schemes, only inspired by the original compression scheme.…”

Section: Features and Invariancesmentioning

confidence: 99%