20 August 1993 Genetic algorithms in hypothesize-and-verify image interpretation
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Proceedings Volume 2059, Sensor Fusion VI; (1993); doi: 10.1117/12.150259
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States
Abstract
Image interpretation plays an important role in computer vision and robotics. We describe here a new approach to image understanding whose novel feature is that it integrates segmentation and interpretation into a single feedback process that incorporates contextual knowledge and uses a genetic algorithm technique to produce an optimal image interpretation. In this paper, we describe the principles of our approach, demonstrate its feasibility, and assess the accuracy of the proposed method using artificially-generated images.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Milan Sonka, Satish K. Tadikonda, Steve M. Collins, "Genetic algorithms in hypothesize-and-verify image interpretation", Proc. SPIE 2059, Sensor Fusion VI, (20 August 1993); doi: 10.1117/12.150259; https://doi.org/10.1117/12.150259
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KEYWORDS
Image segmentation

Genetic algorithms

Image processing

Image fusion

Genetics

Image sensors

Sensor fusion

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