Banknote Image Retrieval Using Rotated QuaternionWavelet Filters

Abstract

A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity.

Keywords:

• discrete wavelet transform (DWT)
• complex wavelet transform (CWT)
• quaternion wavelet transform (QWT)
• rotated quaternion wavelet filters (RQWF)
• feature extraction
• support vector machine (SVM)