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Vision Based Underwater Environment Analysis: A Novel Approach to Estimate Size of Coral Reefs

机译:基于视觉的水下环境分析:一种估计珊瑚礁大小的新方法

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The purpose of our work is to detect and estimate the size of underwater coral reef from image frames using vision based technique. Deep learning architecture is proposed to detect the coral reefs. To extract the frames and build data set, real time underwater video is used. The size of reef is estimated using distance-based algorithm with detected coral information. A nonlinear function is formulated and optimized to get accurate reef size as pixels taken by it in image changes with distance. This algorithm can also be used for real-time analysis of the underwater environment. It is evident from the analysis results and comparison with actual data that the proposed method is accurate in estimating the area occupied by underwater coral reefs.
机译:我们的工作目的是使用基于视觉的技术从图像帧中检测和估计水下珊瑚礁的大小。提出了深度学习架构来检测珊瑚礁。为了提取帧并建立数据集,使用了实时水下视频。珊瑚礁的大小是使用检测到的珊瑚信息的基于距离的算法估算的。制定并优化了非线性函数,以获取准确的礁石尺寸,因为它所拍摄的像素随距离而变化。该算法也可以用于水下环境的实时分析。从分析结果和与实际数据的比较可以明显看出,该方法在估计水下珊瑚礁所占面积方面是准确的。

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