摘要
以NAO机器人为平台,在机器人视觉算法的基础上,研究了NAO机器人的有色目标识别方法。采用基于HSI颜色空间的离散小波变换方式,利用可自动适应阈值Canny算子边缘检测方法和双阈值法提高了图像边缘的准确性和容错性。通过NAO机器人双摄像头系统进行图像的颜色标定,提出的基于模糊系统下证据理论的双摄像机融合策略能够有效地减少颜色之间的标定冲突,将目标图像的识别性能提高约29%。
On the NAO robot platform,this paper focuses on the NAO robot's colored target recognition method based on the research of robot vision algorithm. Using the discrete wavelet transform method based on HSI color space,the Canny operator edge detection method and double threshold method which can automatically adapt to the threshold are used to improve the accuracy and fault tolerance of image edges. Through the NAO robot dual camera system for color calibration of images,the proposed dual camera fusion strategy based on evidence theory in fuzzy system can effectively reduce the calibration conflict between colors and improve the recognition performance of target images by 29%.
引文
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