以差異進化演算法為基礎之機器人目標物顏色即時分割系統

An Object Color Segmentation System for the Robot Based on Differential Evolution Algorithm

許書宇(Hsu, Shu-Yu) ； 許陳鑑(Hsu, Chen-Chien) ； 王偉彥(Wang, Wei-Yen)

《明新學報》 Volume 42 Issue 2 (2016/08) Pp. 1-11

Abstracts

機器人進行目標物追蹤時，時常利用影像分割將目標物從背景中擷取出來，以利後續追蹤。本論文中，我們將影像分割結合差異進化演算法與連通標記法，使機器人得以自行預設目標物HSV色彩閥值，並於後續追蹤過程能即時根據環境亮暗調變HSV閥值。我們以ROBOTIS OP2智慧型人型機器人作為實驗平台，針對五種常用的目標物顏色，包括：紅、黃、綠、藍、紫，來進行實驗評估，以驗證本論文提出之機器人目標物顏色即時分割系統。

Keywords

顏色分割 ； 差異進化演算法 ； 連通標記法 ； 人形機器人

Parallel abstracts

Color segmentation is widely used for recognizing the visual markers in a robotic tracking system. In our contribution, we propose a new method for color segmentation by incorporating differential evolution algorithm and connected component labeling to autonomously preset the HSV threshold of visual markers; then autonomously change the HSV threshold according to the ambient light during the tracking process. To evaluate the effectiveness of the proposed algorithm, a ROBOTIS OP2 humanoid robot is used to conduct the experiment, where five most commonly used color including red, purple, blue, yellow, and green in visual markers are given for comparisons.

Parallel keywords

Color Segmentation ； Differential Evolution ； Connected Component Labeling ； Humanoid Robot

References

Gonzalez, R. C., & Woods, R. E. (2007). Digital image processing (3rd ed). Pearson Educa-tion, Inc.

Horowitz, E., Sahni, S., & Anderson-Freed, S. (2008). Fundamentals of data structures in C. Summit, NJ: Silicon Press.

Kapur, J. N., Sahoo, P. K., & Wong, A. K. C. (1985). A new method for gray - level picture thresholding using the entropy of the histogram. Computer Vision Graphics and Image Process, 29(3), 273-285.

Kurban, T., Civicioglu, P., Kurban, R., & Besdok, E. (2014). Comparison of evolutionary and swarm based computational techniques for multilevel color image thresholding. Applied Soft Computing, 23, 128-143.

Kurugollu, F., Sankur, B., & Harmanci, A. (2001). Color image segmentation using histogram multithresholding and fusion. Image and Vision Computing, 19(13), 915-928.