FPGA-Based Connected Component Algorithm for Vegetation Segmentation

In the process of automatic trees recognition and tracking, image target is captured by RGB camera mounted on a UAV, in processing step image captured is subjected to threshold and extract selected information, This techniques may be applied to recognize objects with different shapes and sizes. In the case of remote sensing vegetation, the image usually contains multiple connected areas or overlapped trees; the proposed system uses the shape characteristics of the image target to self-identify the suspicious overlapped features. This technique allows distinguish, analyze and detect different features in images by assigning a unique label to all pixels that refers to the same entity or object. In the process of automatically recognizing and tracking the target of an image, it is first segmented and extracted. The resulting binary image usually contains several connected regions. The system uses the shape characteristics of the target in the image to automatically identify the suspected overlapped trees. Therefore, it is necessary to detect and evaluate each connected area block separately, in this paper, the improved FPGA-specific rapid marking algorithm is used to detect and extract each connected domain.