融合边缘信息多运动目标检测识别系统设计

运动目标检测算法易受到噪声和亮度变换的影响，从而出现虚假目标，很难满足在实际应用中准确性和实时性的需求。针对上述问题，提出了一种融合边缘信息的多运动目标实时检测算法，并在FPGA平台上构建了视频图像处理系统。该算法首先使用高斯滤波增强算法来提高抗噪性能。然后，采用三帧差分法减少虚假目标的出现概率。同时，对图像进行边缘检测，并将边缘信息与帧差法的结果相融合。最后，运用多目标识别算法完成对运动目标的识别和标记。该算法实现充分利用了FPGA的并行计算和流水线操作，经实验测试检测识别系统能够在1280×720@60Hz视频场景下实现对最多16个运动目标的实时检测。

Design of multi moving target detection and recognition system based on edge information fusion

The motion target detection algorithm is easily affected by noise and changes in brightness, leading to the presence of false targets, making it challenging to meet the requirements of accuracy and real-time performance in practical applications. To address these issues, this paper proposes a real-time multi-object motion detection algorithm that incorporates edge information and constructs a video image processing system on the FPGA platform. The algorithm first utilizes a Gaussian filtering enhancement algorithm to improve noise resistance. Subsequently, the three-frame difference method is employed to reduce the probability of false targets. Simultaneously, edge detection is applied to the images, and the edge information is fused with the results of the frame difference method. Finally, a multi-object recognition algorithm is used to identify and label the moving targets. The algorithm fully utilizes the parallel computation and pipeline operations of FPGA. Experimental tests demonstrate that the detection and recognition system can achieve real-time detection of up to 16 moving targets in 1280×720@60Hz video scenes.