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Adaptive pedestrian detection in infrared images using fuzzy enhancement and top-hat transform

机译:使用模糊增强和礼帽变换的红外图像自适应行人检测

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摘要

Infrared imaging is the order of the day. Infrared imaging finds its applications extensively in defence related areas. Pedestrian detection in IR image is a challenging problem. This paper addresses this problem using fuzzy-based enhancement followed by top-hat transform. The proposed method is adaptive in the sense that the parameters required for the process are calculated adaptively based on the image characteristics. Experimental results on the standard dataset show the robustness of the proposed method with 90% detection rate of pedestrians under different conditions and outperform the other existing methods.
机译:红外成像已成为日常工作。红外成像在国防相关领域得到了广泛的应用。红外图像中的行人检测是一个具有挑战性的问题。本文使用基于模糊的增强,然后进行礼帽变换来解决此问题。从基于图像特征自适应地计算处理所需的参数的意义上来说,所提出的方法是自适应的。在标准数据集上的实验结果表明,该方法的鲁棒性在不同条件下的行人检测率为90%,优于其他现有方法。

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