Interpreting Segmented Laser Radar Images Using a Knowledge-Based System
| Autor: | Nagaraj Nandhakumar, Chen-Chau Chu, Jake K. Aggarwal |
|---|---|
| Rok vydání: | 1990 |
| Předmět: |
business.industry
Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Cognitive neuroscience of visual object recognition computer.file_format Image segmentation Sensor fusion Data conversion Visualization Knowledge-based systems Lidar Segmentation Computer vision Artificial intelligence business computer |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.969985 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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