Abstract

This study presents an efficient method for recognizing object in an image based on Wave Atom Trans-form (WAT). Object recognition is achieved by extracting the energies from all coefficients of WAT. The original image is decomposed by using the WAT. All coefficients are considered as features for the classification process. The extracted features are given as an input to the K-Nearest Neighbor (K-NN) classifier to recognize the object. The evaluation of the system is carried on using Columbia Object Image Library Dataset (COIL-100) database. The classification performance of the proposed system is evaluated by using classification rate in percentage, which is achieved by varying the angle between the views.

Keywords:

Classification rate, feature extraction, KNN classifier , object recognition, wave atom transform,

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Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.