Information extraction from unmanned aerial vehicle (UAV) images has progressed to a great extent. The focus for geospatial data sensing, representation, processing, visualization and information delineation has gradually shifted to UAV, because of its fast delivery with very high spatial resolution data. The users from various fields have started using the UAV data for potential field uses. The land records boundary information delineation is one such case where the UAV images are used for quick and accurate boundary extraction. The extracted boundary is further used as input for the geographical information system (GIS). The fast image acquisition also needs faster and automated information extraction for the technology to meet the societal need. After the image acquisition from the UAV image, the image is segmented using the mean-shift techniques. The best fit segmentation with minimum over and under-segmentation is taken up for automated boundary extraction. The segment boundary coordinates are extracted using the MATLAB image processing tools and represented in vector format using the Geospatial Data Abstraction Library tool. The extracted boundary is compared with the manually digitized boundary with the help of buffers around the reference data and the extracted data. The buffer of 2.0 m is taken up for the completeness, correctness and quality parameter assessment. The completeness, correctness and quality of the extraction are found to be 73.02%, 73.28% and 59.66%, respectively.

中文翻译：

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无人机图像地籍包裹边界提取

从无人机（UAV）图像中提取信息已经取得了很大进展。地理空间数据传感、表示、处理、可视化和信息描绘的重点已逐渐转移到 UAV，因为它具有非常高的空间分辨率数据的快速交付。来自各个领域的用户已经开始将无人机数据用于潜在的现场用途。土地记录边界信息勾画就是这样一种情况，其中无人机图像用于快速准确地提取边界。提取的边界进一步用作地理信息系统 (GIS) 的输入。快速的图像采集也需要更快和自动化的信息提取技术来满足社会需求。从无人机图像中获取图像后，使用均值偏移技术对图像进行分割。具有最小过分割和欠分割的最佳拟合分割用于自动边界提取。使用 MATLAB 图像处理工具提取线段边界坐标，并使用地理空间数据抽象库工具以矢量格式表示。借助参考数据和提取数据周围的缓冲区，将提取的边界与手动数字化的边界进行比较。2.0 m 的缓冲区用于完整性、正确性和质量参数评估。提取的完整性、正确性和质量分别为 73.02%、73.28% 和 59.66%。使用 MATLAB 图像处理工具提取线段边界坐标，并使用地理空间数据抽象库工具以矢量格式表示。在参考数据和提取数据周围的缓冲区的帮助下，将提取的边界与手动数字化的边界进行比较。2.0 m 的缓冲区用于完整性、正确性和质量参数评估。提取的完整性、正确性和质量分别为 73.02%、73.28% 和 59.66%。使用 MATLAB 图像处理工具提取线段边界坐标，并使用地理空间数据抽象库工具以矢量格式表示。借助参考数据和提取数据周围的缓冲区，将提取的边界与手动数字化的边界进行比较。2.0 m 的缓冲区用于完整性、正确性和质量参数评估。提取的完整性、正确性和质量分别为 73.02%、73.28% 和 59.66%。0 m 用于完整性、正确性和质量参数评估。提取的完整性、正确性和质量分别为 73.02%、73.28% 和 59.66%。0 m 用于完整性、正确性和质量参数评估。提取的完整性、正确性和质量分别为 73.02%、73.28% 和 59.66%。