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An Efficient Hardware-Oriented Single-Pass Approach for Connected Component Analysis

1
Department of Informatics, Modeling, Electronics and System Engineering, University of Calabria, 87036 Rende, Italy
2
Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3055; https://doi.org/10.3390/s19143055
Received: 3 June 2019 / Revised: 4 July 2019 / Accepted: 9 July 2019 / Published: 11 July 2019
(This article belongs to the Section Intelligent Sensors)
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PDF [4406 KB, uploaded 11 July 2019]
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Abstract

Connected Component Analysis (CCA) plays an important role in several image analysis and pattern recognition algorithms. Being one of the most time-consuming tasks in such applications, specific hardware accelerator for the CCA are highly desirable. As its main characteristic, the design of such an accelerator must be able to complete a run-time process of the input image frame without suspending the input streaming data-flow, by using a reasonable amount of hardware resources. This paper presents a new approach that allows virtually any feature of interest to be extracted in a single-pass from the input image frames. The proposed method has been validated by a proper system hardware implemented in a complete heterogeneous design, within a Xilinx Zynq-7000 Field Programmable Gate Array (FPGA) System on Chip (SoC) device. For processing 640 × 480 input image resolution, only 760 LUTs and 787 FFs were required. Moreover, a frame-rate of ~325 fps and a throughput of 95.37 Mp/s were achieved. When compared to several recent competitors, the proposed design exhibits the most favorable performance-resources trade-off. View Full-Text
Keywords: connected component analysis; features extraction; FPGAs; embedded systems connected component analysis; features extraction; FPGAs; embedded systems
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Spagnolo, F.; Perri, S.; Corsonello, P. An Efficient Hardware-Oriented Single-Pass Approach for Connected Component Analysis. Sensors 2019, 19, 3055.

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