Abstract
Detecting straight lines in video plays a fundamental role in camera-based industrial automation. With the increasing demands on production efficiency, detection speed becomes one of the bottlenecks for highly-efficient industrial automation. Because of data dependency and hardware limitation, existing vision systems based on CPU/GPU are unable to detect straight lines at ultra-high speed. This paper addresses this problem and proposes a hardware-friendly Hough transform that can be implemented in fully parallel for ultra-high-speed detection, because of two key features: 1) It processes multiple pixels in parallel and directly calculates line parameters while capturing the current frame; 2) it simultaneously initializes Hough parameter space and votes in Hough parameter space without any delay. Based on the proposed hardware-friendly Hough transform, its chip-level implementation and system-level hardware design are presented. Experimental results show that the main benefits of the proposed architecture are in real-time performances of high frame rate (784 FPS) and ultra-low delay (0.7749 ms/frame).
Original language | English |
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Journal | IEEE Transactions on Industrial Informatics |
DOIs | |
Publication status | Accepted/In press - 2022 |
Keywords
- Automation
- Delays
- Field programmable gate arrays
- Hardware
- High frame rate
- Image edge detection
- parallel Hough transform
- Standards
- straight-line detection
- Transforms
- ultra-low delay
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Computer Science Applications
- Electrical and Electronic Engineering