Affiliations: [a] Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung, Taiwan | [b] Department of Electrical Engineering, National Central University, Taoyuan, Taiwan | [c] Digital Information Research Labs., Chennai, India
Correspondence:
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Corresponding author: Yao-Liang Chung, Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung City, Taiwan. E-mail: ylchung@email.ntou.edu.tw.
Abstract: This study aimed to apply a microprocessor on a wireless automated vehicle to achieve real-time tracking of moving objects. The targets captured by the camera on the vehicle were first separated from their background through background subtraction. Next, morphological processing was performed to remove unnecessary information. An enhanced seeded region growing method was used to achieve image segmentation by labeling and segmenting the targets effectively, thus enhancing the accuracy and resolving the problem of object concealment. The corresponding red, green, and blue colors of each target were calculated through a color space, which was then converted into an enhanced luminance/chroma blue/chroma red (YUV) color space for color histogram modeling and storage, so as to increase the system’s tracking speed. The enhanced YUV colors also achieved accurate tracking in dark places. After inputting the next image, an enhanced agglomerative hierarchical clustering method was used to agglomerate and connect pixels with the same YUV for tracking. A proportional-integral-derivative controller controlled the motors on the camera lens and the vehicle so that the target could be tracked properly in real-time. The experimental results revealed that our proposed tracking method performed better than conventional tracking methods.
Keywords: Object tracking, seeded region growing method, YUV color space, agglomerative hierarchical clustering method, PID control
