【摘要】 目标区域多维特征的建模表征是实现目标跟踪搜索的前提。传统的特征提取方法通常先连通出目标区域，再计算目标特征，实时性不强。提出了一种基于像素的连通域标记及目标特征同步计算方法，建立特征传递机制，利用标号映射表关联标号表与特征属性表，并在区域邻接时进行标号合并和特征属性同步传递计算，保证了目标区域连通完成即可输出目标区域特征。给出一种基于FPGA硬件设计的实现方案。仿真测试结果显示，此方法具有以下几方面优势：连通域标记耗时少，仅为（L×W+2n/m）×T_clk，接近理论最小值（L×W）×T_clk；利用循环缓存区存储图像，资源消耗小；标记与计算并行处理，提升了检测跟踪效率；多目标特征经测试验证结果准确，可有效支持后续的目标跟踪检测；具有理论与实用价值。更多还原

【Abstract】 The prerequisite of target detection and tracking is to model and represent the target based on multi-dimensional features extracted from the target region. The traditional target feature extraction needs to connect the target region first and then must calculate the target feature, which has still room for improvement in real-time performance. An advantage of the new method based on the synchronous calculation of pixel-connected domain markers and target features is that the target features can be output when the target region is connected. This article proposes a method highlighting pixel-based marking of connection domains and synchronous computation of target features, which can output target features immediately after target areas are connected. By setting up a feature transfer mechanism, this method establishes a marker table, a marker mapping table and a feature attributes table while scanning images, and links the marker mapping table and the feature attributes table with the help of the marker table. When different areas are adjacent to one another, markers are consolidated while the features’ attributes are synchronously transferred and computed, ensuring real-time extraction of the target features. Regarding real-time and multiple-dimensional extraction of the features of multiple targets in high-resolution distant sensing images, the article proposes an implementation plan based on FPGA hardware design. According to the results of a number of simulation tests, the method featuring highspeed marking of connection domains over one iteration of split pixels and real-time computing of target features boasts the following outstanding characteristics: The time consumed by marking connection domains is only（L × W + 2n/m） × T_clk, close to the theoretical minimum（L × W） × T_clk; saving images in cyclical buffers only takes up few resources; parallel pipeline processing of marking and computation improves the detection and tracking efficiency; the test results of multiple target features are accurate and consequently can effectively support subsequent target tracing detections; and the method also has both theoretical and practical values.更多还原