DOI: 10.36347/sjet.2018.v06i07.004

Pages: 242-245

Aiming at the limitations of using fixed threshold and the complex calculation process in SUSAN operator. An adaptive SUSAN corner detector based on lifting wavelet transform is proposed in the paper. According to the corner properties in an image, the theory of lifting w- avelet transform is adopted to process the image. It will be more effective that the corner candidates are obtained from the high frequency information, which can reduce the searching range for corners. The new algorithm is self-adaptive to adjust the intensity discrepancy between the core point and its epsilon neighborhood pixels. Experiment demonstrates that the proposed corner detector is faster and more effective than traditional SUSA N algorithm.