An algorithm to recognize the target object contour based on 2D point clouds by laser-CCD-scanning
| Autor: | Duan-wei Shi, Yuxiang Xu, Fan Feng, Shiyu Chen, Pan Xu, Ji Zhou, Hongyong Mao |
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| Rok vydání: | 2015 |
| Předmět: |
Multidisciplinary
Computer science business.industry System of measurement Binary image ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Point cloud Corner detection Reverse transformation Object contour Laser law.invention law Computer vision Artificial intelligence Invariant (mathematics) business Algorithm |
| Zdroj: | Wuhan University Journal of Natural Sciences. 20:355-361 |
| ISSN: | 1993-4998 1007-1202 |
| DOI: | 10.1007/s11859-015-1105-x |
| Popis: | For a vision measurement system consisted of laser-CCD scanning sensors, an algorithm is proposed to extract and recognize the target object contour. Firstly, the two-dimensional (2D) point cloud that is output by the integrated laser sensor is transformed into a binary image. Secondly, the potential target object contours are segmented and extracted based on the connected domain labeling and adaptive corner detection. Then, the target object contour is recognized by improved Hu invariant moments and BP neural network classifier. Finally, we extract the point data of the target object contour through the reverse transformation from a binary image to a 2D point cloud. The experimental results show that the average recognition rate is 98.5% and the average recognition time is 0.18 s per frame. This algorithm realizes the real-time tracking of the target object in the complex background and the condition of multi-moving objects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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