Contact address E-mail: Ferdous.Sohel@infotech.monash.au

1. G B B C P Q D A K H A D BK BA s r E F Region 2 Region 1 Region 3 1 pel Shape Codec WHAT IS THE MINIMUM DISTANCE OF POINT B FROM LINE AD ?? OBJECTIVE of this WORK QUALITY Which one is BETTER ? So The SHORTEST ABSOLUTE DISTANCE alone cannot do ALL What is the distortion at the corners ?? 3.1 pel !!! A Modified Distortion Measurement Algorithm for Shape Coding Ferdous A. Sohel, Prof. Laurence S. Dooley and Dr. Gour C. KarmakarGippsland School of Computing and Information SystemMonash University, Churchill. Victoria 3842 Contact address E-mail: Ferdous.Sohel@infotech.monash.edu.au Step 1 Abstract Efficient encoding of object boundaries has become increasingly prominent in areas such as content-based storage and retrieval, studio and television post-production facilities, mobile communications and other real-time multimedia applications. The way distortion between the actual and approximated shapes is measured however, has a major impact upon the quality of the shape coding algorithms. In existing shape coding methods, the distortion measure do not generate an actual distortion value, so this paper proposes a new distortion measure, called a modified distortion measure for shape coding (DMSC) which incorporates an actual perceptual distance. The performance of the Operational Rate Distortion optimal algorithm [1] incorporating DMSC has been empirically evaluated upon a number of different natural and synthetic arbitrary shapes. Both qualitative and quantitative results confirm the superior results in comparison with the ORD algorithm for all test shapes, without any increase in computational complexity. (1) (2) Step 2 • If the shape point is in region 1 (opposite side of the perpendicular lines) use the shortest absolute distance as the distortion metric, d (A, D, Shape_point). • Else if it is inregion 2 same side of the perpendicular lines and close to End point A use the direct Euclidean distortion measure d (A, Shape_point). EQ: (2). • Else use the direct Euclidean distortion measure d (D, Shape_point). EQ: (2). • Challenges: • Measure the actual distance of a particular point from an edge. • Hence, measure the accurate distortion at that particular shape point while approximating the shape using polygons. Results Given maximum distortion = 1 pel • Motivation: • Operational-Rate-Distortion based Shape coding is a challenging task. • A correct distortion metric is important to ensure the quality of the encoding system. • The existing ORD shape coding algorithms (e.g., [1]) use the shortest absolute distance as the distortion metric. It cannot always calculate the distortion correctly specially, for the shapes having sharp corners. DMSC-D_mx=1 pel [1]- D_max=10 pel How DMSC Works: Step 1: Find the Position of the shape point with respect to the approximating polygon. - Draw perpendicular lines through the end-points of the approximating line. - Determine the region where the shape point belongs to. Step 2: Measure the distance in accordance with the region (position of the shape). Step 3: Use this distortion hence forth in the ORD algorithms [1]. [1]- D_max=1.4pel DMSC- D_max=1 pel DMSC- D_max=2 pel [1]- D_max=4.5 pel Given D_max = 3 pel DMSC- D_max=3 pel Given D_max = 2 pel [1]- D_max >3pel • Conclusions: • Accurately calculate the distortion. • Can be seamlessly integrated into the ORD algorithms [1]. • Makes guarantee on the distortion measurements. • Has the same computational complexity order of the Shortest absolute distance metric. Reference: [1]. A.K. Katsaggelos, L.P. Kondi, F.W. Meier, J. Ostermann, and G.M. Schuster, “MPEG-4 and Rate-Distortion-Based Shape-Coding Techniques,” Proceedings of IEEE, vol. 86, pp. 1126-1154, June 1998.