Paper
27 March 1989 A Class Of Iterative Thresholding Algorithms For Real-Time Image Segmentation
M. H. Hassan
Author Affiliations +
Proceedings Volume 1002, Intelligent Robots and Computer Vision VII; (1989) https://doi.org/10.1117/12.960272
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States
Abstract
Thresholding algorithms are developed for segmenting gray-level images under nonuniform illumination. The algorithms are based on learning models generated from recursive digital filters which yield to continuously varying threshold tracking functions. A real-time region growing algorithm, which locates the objects in the image while thresholding, is developed and implemented. The algorithms work in a raster-scan format, thus making them attractive for real-time image segmentation in situations requiring fast data throughput such as robot vision and character recognition.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. H. Hassan "A Class Of Iterative Thresholding Algorithms For Real-Time Image Segmentation", Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); https://doi.org/10.1117/12.960272
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Robot vision

Chromium

Computer vision technology

Machine vision

Image processing algorithms and systems

Instrument modeling

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