Name
Title | ||
|---|---|---|
An Efficient Hardware-Oriented Single-Pass Approach for Connected Component Analysis. |
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 x 480 input image resolution, only 760 LUTs and 787 FFs were required. Moreover, a frame-rate of similar to 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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19143055 | SENSORS |
Keywords | Field | DocType |
connected component analysis,features extraction,FPGAs,embedded systems | Single pass,System on a chip,Image frame,Field-programmable gate array,Hardware acceleration,Engineering,Throughput,Computer hardware,Connected-component labeling,Image resolution | Journal |
Volume | Issue | Citations |
19 | 14 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fanny Spagnolo | 1 | 8 | 4.00 |
| Stefania Perri | 2 | 264 | 33.11 |
| Pasquale Corsonello | 3 | 278 | 38.06 |