Paper
8 July 2011 Vision-based obstacle recognition system for automated lawn mower robot development
Zalhan Mohd Zin, Ratnawati Ibrahim
Author Affiliations +
Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80092K (2011) https://doi.org/10.1117/12.896146
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China
Abstract
Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zalhan Mohd Zin and Ratnawati Ibrahim "Vision-based obstacle recognition system for automated lawn mower robot development", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80092K (8 July 2011); https://doi.org/10.1117/12.896146
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Cited by 2 scholarly publications.
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KEYWORDS
Image processing

Image segmentation

Neodymium

Image filtering

Databases

Robot vision

Digital image processing

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