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


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。

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.


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