Object Detection by 2-D Continuous Wavelet Transform
Vijaya Kumar Reddy, Kiran Kumar Siramoju, Pradip Sircar · 2014
The use of two dimensional (2-D) continuous wavelet analysis has not been extensive for image processing using wavelets. It has been overshadowed by the 2-D discrete dyadic wavelet transform (DWT) due to its compactness and excellent performance in coding, data compression, image reconstruction, etc. However, the 2-D DWT has some restrictions on the scale and position parameters, and it does not detect all the features of an image unless properly tuned. The 2-D continuous wavelet transform (CWT), on the other hand, is more flexible and provides complete control over the scale and position parameters, and thus it is capable of extracting various features of an image, which cannot be accomplished by the DWT. It is shown that sharp edges can be extracted at lower scales of the 2-D CWT. In this paper, an algorithm is developed to detect focused objects in an image/video using the 2-D CWT. The first step in this algorithm is to extract the edges of focused objects using the 2-D CWT. The object detected is converted to binary image. Some applications of object detection method in image and video processing are mentioned.