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Department of Computer Science Seminar
2012 Series

2D Finite Rate of Innovation Reconstruction Method for Step Edge and Polygon Signals in the Presence of Noise

Mr. Changsheng Chen
PhD Candidate, the School of Electrical and Electronic Engineering
Nanyang Technological University

Date: September 11, 2012 (Tuesday)
Time: 3:30 - 4:30 pm
Venue: SCT714, Cha Chi Ming Science Tower, Ho Sin Hang Campus

The finite rate of innovation principle is developed for sampling a class of non-bandlimited signals that have a finite number of degrees of freedom per unit of time, i.e., signals with FRI. This sampling scheme is later extended to three classes of sampling kernels with compact support and applied to the step edge reconstruction problem by treating the image row by row. In this paper, we regard step edges as 2D FRI signals and reconstruct them block by block. The step edge parameters are obtained from the 2D moments of a given image block. Experimentally, our technique can reconstruct the edge more precisely and track the Cramér–Rao bounds closely with a signal-to-noise ratio larger than 4 dB on synthetic step edge images. Experiments on real images show that our proposed method can reconstruct the step edges under practical conditions, i.e., in the presence of various types of noise and using a real sampling kernel. The results on locating the corners of data matrix barcodes using our method also outperform some state-of-the-art barcode decoders.

Changsheng Chen (S’09) received the B.Eng. degree in software engineering from Sun Yat-sen University, Guangzhou, China, in 2008. He is currently working towards the Ph.D. degree at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His current research interests include 2D barcode, digital image enhancement, image quality measure, pattern recognition, and information security. Mr. Chen serves as a Reviewer for the IEEE Transactions on Image Processing, the IEEE Transactions on Signal Processing, the IEEE Transactions on Information, Forensic and Security; and the IEEE Signal Processing Letter.

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