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Adaptive centre extraction method for structured light stripes

1,2Zhixin Hu, 1Hongtao Zhu, 3Ming Hu and 4Yong Ma

1School of Mechanical and Electrical Engineering, Nanchang University, Nanchang, Jiangxi Province, China
2School of Mechanical and Vehicular Engineering, Nanchang Institute of Science and Technology, Nanchang, Jiangxi Province, China
3School of Electronic Engineering, Nanchang Institute of Science and Technology, Nanchang, Jiangxi Province, China
4Electronic Information School, Wuhan University, Wuhan, Hubei Province, China

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Abstract. In the vision systems based on structured light, accurate extracting of centre positions of a light stripe represents one of the key points in solving the whole measurement task. Usually, high radiant illumination and objects with abundant surface textures decrease the detection precision. To address these problems, we suggest an adaptive centre-extraction method. First, it improves the image contrast using a novel adaptive threshold-based power transformation. Second, pixel-level centre points are obtained with our adaptive dual-threshold Canny’s edge detection method. Finally, subpixel-level centre points are extracted using a Hessian matrix for a limited number of pixels. Our experiments prove robustness and practicability of the method, which can cope with complex surface textures of projected objects and high radiant illumination.

Keywords: structured light, radiant illumination, centre extraction, power transform, Hessian matrix

PACS: 42.30.Tz
UDC: 004.932
Ukr. J. Phys. Opt. 18 9-19
doi: 10.3116/16091833/18/1/9/2017
Received: 13.04.2016
After revision: 08.11.2016

Анотація. У системах зору, що працюють у структурованому світлі, одним із ключових моментів у вирішенні задачі вимірювань є точне визначення позицій центра світлої смуги. Надмірна текстурованість поверхні проектованих об’єктів і висока освітленість зазвичай понижують відповідну точність. Для вирішення цих проблем запропоновано адаптивний метод екстракції центра. По-перше, він підвищує контраст зображення за допомогою нового адаптивного степеневого перетворення, заснованого на порозі. По-друге, центральні точки на рівні пікселів отримують за допомогою адаптивного методу Кенні з подвійним порогом для виявлення краю. Нарешті, центральні точки на рівні субпікселів знаходять за допомогою матрицю Гессе для обмеженої кількості пікселів. Наші експерименти довели надійність і практичну виправданість цього методу, який ефективно працює з ускладненими поверхневими текстурами проектованих об’єктів, а також за умов високої освітленості.
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