Constructing long edge segments for object recognition

Bryan D. Mielke; Neelima Shrikhande

doi:10.1117/12.130979

1 August 1992 Constructing long edge segments for object recognition

Bryan D. Mielke, Neelima Shrikhande

Proceedings Volume 1778, Imaging Technologies and Applications; (1992) https://doi.org/10.1117/12.130979
Event: Optical Engineering Midwest 1992, 1992, Chicago, IL, United States

Abstract

Most computer vision algorithms need a good edge description of the scene. The edges are used for high level object recognition. The image of the object is preprocessed to extract edges. Often the extracted edges are short and noisy. This paper describes an algorithm that groups edgelets together to aid in higher level vision object recognition. The input consists of two dimensional and three dimensional range data points from the image of the object. This data is used in testing the edges for grouping properties. These properties include parallelism, collinearity, proximity, and segment length. Short edges are combined into longer line segments using the above criteria. Results are reported for synthetic and real data.

Citation Download Citation

Bryan D. Mielke and Neelima Shrikhande "Constructing long edge segments for object recognition", Proc. SPIE 1778, Imaging Technologies and Applications, (1 August 1992); https://doi.org/10.1117/12.130979

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