RECOGNITION OF 2D STANDALONE AND OCCLUDED OBJECTS USING WAVELET TRANSFORM
K.M. Tsang · International Journal of Pattern Recognition and Artificial Intelligence · 2001
A planar curve descriptor which is invariant to translation, size, rotation and starting point in tracing the boundary is developed based on the periodized wavelet transform. Coefficients obtained from the transform are divided into different bands, and feature vectors are extracted for the recognition of two-dimensional closed boundary curves. The weight vectors which include the width of different bands are also derived to differentiate spurious results arising from noisy samples. The technique is further extended for the recognition of occluded objects by incorporating local features into the features vector to form a feature map. Matching the likeliness of a part of the feature map with that of the reference feature maps indicates which class the occluded object belongs to. Experimental results were obtained to show the effectiveness of the proposed technique.