Detection algorithm fusion concepts for computer vision

David P. Casasent; Anqi Ye; Ashit Talukder

doi:10.1117/12.222659

3 October 1995 Detection algorithm fusion concepts for computer vision

David P. Casasent, Anqi Ye, Ashit Talukder

Proceedings Volume 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling; (1995) https://doi.org/10.1117/12.222659
Event: Photonics East '95, 1995, Philadelphia, PA, United States

Abstract

We consider detection (locating all objects in a scene) independent of object distortions and contrast differences and in the presence of clutter. We employ several different new detection algorithms; to reduce false alarms. We fuse (combine) the outputs from different detection algorithms. We describe a new peak sorting detection scoring algorithm and 3 different fusion algorithms to combine the results from different algorithms: binary, analog, and hierarchical fusion. Quantitative data on a distortion-invariant six object class is presented; the objects have a wide range of object contrasts including obscured objects and the objects are present in severe clutter.

Citation Download Citation

David P. Casasent, Anqi Ye, and Ashit Talukder "Detection algorithm fusion concepts for computer vision", Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); https://doi.org/10.1117/12.222659

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