Knowledge-based automatic extraction of multi-structured light stripes
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To achieve automatic processing of the multi-structured light stripe images, we need to extract many stripes automatically in a short time. However, due to the complexity and diversity of its work, the related research progress is very slow. Therefore, we first use the Radon transformation and grayscale transform enhancement to eliminate noise in images. Then, a new and adaptive feature model is created based on the knowledge of stripes distribution. The distribution of the stripes is matched by the model, and then the target stripe regions are picked up to realize the extraction of the stripes. In the actual verification, the qualified rate of the detection is basically over 80%, and the detection time is controlled at about 2 s. The automatic extraction of target stripes effectively avoids the tedious work that workers need to do it manually, and it is of great significance for the application of multi-structured light detection technology.
KeywordsAutomatic extraction Manual contouring Multi-structured light stripes Knowledge model
This work was supported by the National Natural Science Foundation Program of China (no. 51575523). I am deeply indebted to a number of people. The thesis would not have been completed without their assistance and encourage. I am profoundly grateful to my tutor, Professor Tang, whose instruction and advice have guided me through each step of my writing. My great gratitude also goes to some of my teachers and friends who are selfless and generously helped me with my thesis. They are Professor Cao, Professor Shao, Dr. Deng, Professor Wang, Teacher Su, etc.
Compliance with ethical standards
This study was funded by the National Natural Science Foundation Program of China (Grant number no. 51575523).
Conflict of interest
Author Chao Ding declares that he has no conflict of interest. Author Liwei Tang declares that he has no conflict of interest. Author Lijun Cao declares that he has no conflict of interest. Author Xinjie Shao declares that he has no conflict of interest. Author Wei Wang declares that he has no conflict of interest. Author Shijie Deng declares that he has no conflict of interest. We declare that we do not have any commercial interest that represents a conflict of interest in connection with the work submitted.
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