Neural network in a multi-agent system for line detection task in images

P. V. Babayan; N. Yu. Shubin

doi:10.1117/12.2518410

13 May 2019 Neural network in a multi-agent system for line detection task in images

P. V. Babayan, N. Yu. Shubin

Proceedings Volume 10995, Pattern Recognition and Tracking XXX; 1099504 (2019) https://doi.org/10.1117/12.2518410
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Lines are one of the most informative structure elements in any images. For this reason, objects detection and recognition problem are often reduced to edge detection task. Radon transform and Hough transform are widely used in straight-line detection. However, these methods allow estimating only the straight line parameters (but not line segment). It is proposed to split the image into square fragments (blocks) in which straight-line segments are detected to solve this problem. A multi-agent system is used to combine segments into curves and drop false detections. The use of artificial neural networks (NN) for programming a part of agent behavior in the multi-agent system is the main theme of this work.

Conference Presentation

Citation Download Citation

P. V. Babayan and N. Yu. Shubin "Neural network in a multi-agent system for line detection task in images", Proc. SPIE 10995, Pattern Recognition and Tracking XXX, 1099504 (13 May 2019); https://doi.org/10.1117/12.2518410

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