Paper Money Recognition Using Pixel-Based Analysis

This paper presents a novel approach in bill (paper money) image matching based on middle-level features, instead of low-level features. The approach is developed utilizing edge pixel neighboring histograms for capturing the overall image structure. The closeness of the method to human perceptual judgment is evaluated by a subjective test along with the efficiency in comparison with three other methods known from the iterature. The query set and the image database used in the tests are scanned, photographed, or collected from the web. Experimental results show a significant supremacy in semantic compatibility over the MPEG- 7’s edge histogram descriptor (EHD) and the invariant moment’s method. The proposed method is more efficient than the correlation method which is closer to human perception.

Keywords:

Image analysis , Edge pixels , Bill image recognition , Semantic evaluation.