To enhance precision and comprehensiveness in identifying targets in electric power construction monitoring video, a novel target recognition algorithm utilizing infrared imaging is explored. This algorithm employs a color processing technique based on a local linear mapping method to effectively recolor monitoring images. The process involves three key steps: color space conversion, color transfer, and pseudo-color encoding. It is designed to accentuate targets in the infrared imaging. For the refined identification of these targets, the algorithm leverages a support vector machine approach, utilizing an optimal hyperplane to accurately predict target types. We demonstrate the efficacy of the algorithm, which achieves high target recognition accuracy in both outdoor and indoor electric power construction monitoring scenarios. It maintains a false recognition rate below 3% across various environments.

翻译：为提高电力施工监控视频中目标识别的精确度与全面性，探索了一种基于红外成像的新型目标识别算法。该算法采用基于局部线性映射方法的色彩处理技术，有效对监控图像进行重着色。处理过程包含三个关键步骤：色彩空间转换、色彩传递及伪彩色编码。其设计旨在突出红外成像中的目标。针对这些目标的精细化识别，算法采用支持向量机方法，利用最优超平面精确预测目标类型。我们验证了该算法的有效性，其在室外和室内电力施工监控场景中均能实现高准确度的目标识别，并在各类环境中将误识别率保持在3%以下。