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Wavelet correlogram: a new approach for image indexing and retrieval,
- J. Elsevier Pattern Rec.
, 2005
"... Summary Storage and retrieval of images in digital libraries become a real demand in industrial, medical, and other applications. Current image indexing and retrieval systems are based on two major approaches including spatial and transform domain-based methods. The first approach usually uses pixe ..."
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Cited by 4 (1 self)
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Summary Storage and retrieval of images in digital libraries become a real demand in industrial, medical, and other applications. Current image indexing and retrieval systems are based on two major approaches including spatial and transform domain-based methods. The first approach usually uses pixel (or a group of adjacent pixels) features like color and shape, while the second approach uses the data in transform domain such as wavelets. This paper presents a new algorithm for content-based image indexing and retrieval to be used in digital libraries. The proposed method is based on a combination of multiresolution image decomposition and color correlation histogram. According to the new algorithm, wavelet coefficients of the image are computed first using a directional wavelet transform. We propose the use of 2D Gabor functions since they achieve the theoretical limit for conjoint resolution on information in the 2D spatial and 2D Fourier domains. A quantization step is then applied before computing one-directional autocorrelograms of the wavelet coefficients. Finally, index vectors are constructed using these one-directional wavelet correlograms.
Automated, Transformation Invariant, Shape Recognition through Wavelet Multiresolution
"... The purpose of this study is to demonstrate the e#ciency of Wavelet Multi-Resolution Analysis (W-MRA) applied to automated shape recognition in an automatic vehicle driving scheme. Di#erent types of shapes have to be recognized in this framework. They pertain to most of the objects entering the sens ..."
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Cited by 1 (0 self)
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The purpose of this study is to demonstrate the e#ciency of Wavelet Multi-Resolution Analysis (W-MRA) applied to automated shape recognition in an automatic vehicle driving scheme. Di#erent types of shapes have to be recognized in this framework. They pertain to most of the objects entering the sensors field of a car. These objects can be road signs, lane separation lines, moving or static obstacles, other automotive vehicles, or visual beacons. The recognition process must be invariant to global, a#ne or not, transformations which are : rotation, translation, scaling and perspective (wide angle camera lenses). It also has to be invariant to more local, elastic, deformations due to environmental conditions (weather : rain, mist, light reverberation) as well as optical or electrical noise.
