FPGA-Based Connected Component Algorithm for Vegetation Segmentation
Fatima Zahra Bassine1, Ahmed Errami2, Mohamed Khaldoun3
1Fatima Zahra Bassine*, Electrical Department, NEST Research Group, ENSEM, Hassan II University Casablanca, Morocco.
2Ahmed Errami, Electrical Department, NEST Research Group, ENSEM, Hassan II University Casablanca, Morocco.
3Mohamed Khaldoun, Electrical Department, NEST Research group, ENSEM, Hassan II University Casablanca, Morocco.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 26, 2019. | Manuscript published on January 10, 2020. | PP: 2422-2427 | Volume-9 Issue-3, January 2020. | Retrieval Number: C7993019320/2020©BEIESP | DOI: 10.35940/ijitee.C7993.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Precision Agriculture, Segmentation, Connected Components, FPGA.
Scope of the Article: Algorithm Engineering