Applied region restriction and noncausal algorithm for line process of image sequence

Yasuhisa Kohno; Takumi Ebine; Nozomu Hamada

doi:10.1117/12.411558

28 December 2000 Applied region restriction and noncausal algorithm for line process of image sequence

Yasuhisa Kohno, Takumi Ebine, Nozomu Hamada

Proceedings Volume 4115, Applications of Digital Image Processing XXIII; (2000) https://doi.org/10.1117/12.411558
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

The precise estimation of optical flow is a key technology in computer vision and moving image processing. Due to the inherent feature of apparent motion occlusion and uncovered phenomena, flow estimation is erroneous at moving object's boundary. The line field lattice process(i.e. Gibbs/Markov random field model of discontinuity) is a well-known solution to this problem.The binary-valued line is used to separate regions with respect to motion. This paper proposes two improvements to the conventional line field estimation process. One is to reduce the computational burden by the following idea. At the MAP estimation algorithm for region segmentation, the applied region of line setting is restricted solely within motion boundary area which is specified by thresholding the residue of optical flow constraints. The second improvement is to refine the estimation accuracy at the recursive minimization of energy function. Since the previous pel-recursive line estimation procedure uses causal scanning, it tends to give undesirable lines such as cracked or isolated lines.Our proposal algorithm adopts non-causal scan process. The effect of the proposed methods are examined for artificial and a real moving image. In consequence, only 14 of computational time of previous method is necessary to generate the line. In addition, undesirable line setting is effectively omitted.

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Yasuhisa Kohno, Takumi Ebine, and Nozomu Hamada "Applied region restriction and noncausal algorithm for line process of image sequence", Proc. SPIE 4115, Applications of Digital Image Processing XXIII, (28 December 2000); https://doi.org/10.1117/12.411558

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KEYWORDS

Image processing

Optical flow

Magnetorheological finishing

Motion estimation

Motion models

Image segmentation

Motion detection

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