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The application of image mosaic in information collecting for an amphibious spherical robot system

机译:图像拼接在水陆两栖机器人系统信息采集中的应用

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Amphibious spherical robots that achieve the correct navigation need to collect surround information and clear perception. In addition to equip various sensors, the robot collecting information can also rely on the video images, which include rich texture and information of color. In this paper, we present a video image mosaic method to collect surrounding information of the amphibious spherical robot. We extract key frame from video image based on K-means clustering, and control the number of key frame by changing threshold. Meanwhile, pre-processing key frame and extracting the image key points based on SIFT (Scale-invariant Feature Transform). Then, use RANSAC (Random Sample Consensus) to eliminate the mismatch, and choose suitable value of scaling parameter of SIFT to improve match accuracy. Finally, stitching these key frames up, we got a complete image. Experimental results indicated that image mosaic not only conclude key points of video but also reduce fuzzy phenomenon, enhance the perception of direction. Compared with the direct splicing of video frames, the computation is greatly reduced and still retains important information.
机译:实现正确导航的两栖球形机器人需要收集周围的信息并获得清晰的感知。除了配备各种传感器外,机器人收集信息还可以依靠视频图像,其中包括丰富的纹理和颜色信息。在本文中,我们提出了一种视频图像拼接方法来收集两栖球形机器人的周围信息。我们基于K-means聚类从视频图像中提取关键帧,并通过更改阈值来控制关键帧的数量。同时,基于SIFT(尺度不变特征变换)对关键帧进行预处理并提取图像关键点。然后,使用RANSAC(随机样本共识)消除不匹配,并选择合适的SIFT缩放参数值以提高匹配精度。最后,将这些关键帧缝合起来,我们得到了完整的图像。实验结果表明,图像拼接不仅可以总结视频的关键点,而且可以减少模糊现象,增强方向感。与直接拼接视频帧相比,计算量大大减少,并且仍保留重要信息。

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