Recognition of similar objects using 2-D wavelet-fractal feature extraction | IEEE Conference Publication | IEEE Xplore

Recognition of similar objects using 2-D wavelet-fractal feature extraction


Abstract:

A new two dimensional (2-D) object recognition method is proposed to differentiate similar objects, detect defective objects, and recognize printed characters. First, a 2...Show More

Abstract:

A new two dimensional (2-D) object recognition method is proposed to differentiate similar objects, detect defective objects, and recognize printed characters. First, a 2-D image is transformed to a weighted shape matrix to secure invariance in translation, scaling, rotation, and split into four dyadic subimages. Wavelet transformation is applied to each subimage in order to further explore its details in different directions and to achieve image subband decomposition. Finally, an efficient and effective 2-D image fractal algorithm is used to extract each subband coefficient as a feature for classification. A series of experiments were conducted on binary objects and character images for recognition and classification. The experimental results showed that the proposed method is especially effective in classifying similar objects and the recognition rate could be very high in the recognition of printed characters.
Date of Conference: 11-15 August 2002
Date Added to IEEE Xplore: 10 December 2002
Print ISBN:0-7695-1695-X
Print ISSN: 1051-4651
Conference Location: Quebec City, QC, Canada

References

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