Interpreting Segmented Laser Radar Images Using a Knowledge-Based System

Chen-Chau Chu; N. Nandhakumar; J. K. Aggarwal

doi:10.1117/12.969985

1 March 1990 Interpreting Segmented Laser Radar Images Using a Knowledge-Based System

Chen-Chau Chu, N. Nandhakumar, J. K. Aggarwal

Proceedings Volume 1198, Sensor Fusion II: Human and Machine Strategies; (1990) https://doi.org/10.1117/12.969985
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

This paper presents a knowledge-based system (KBS) for man-made object recognition and image interpretation using laser radar (ladar) images. The objective is to recognize military vehicles in rural scenes. The knowledge-based system is constructed using KEE rules and Lisp functions, and uses results from pre-processing modules for image segmentation and integration of segmentation maps. Low-level attributes of segments are computed and converted to KEE format as part of the data bases. The interpretation modules detect man-made objects from the background using low-level attributes. Segments are grouped into objects and then man-made objects and background segments are classified into pre-defined categories (tanks, ground, etc.) A concurrent server program is used to enhance the performance of the KBS by serving numerical and graphics-oriented tasks for the interpretation modules. Experimental results using real ladar data are presented.

Citation Download Citation

Chen-Chau Chu, N. Nandhakumar, and J. K. Aggarwal "Interpreting Segmented Laser Radar Images Using a Knowledge-Based System", Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, (1 March 1990); https://doi.org/10.1117/12.969985

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