Journal ArticleDOI
A Multi-Resolution FPGA-Based Architecture for Real-Time Edge and Corner Detection
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TLDR
A performance analysis of the FPGA and the GPU implementations, and an extra CPU reference implementation, shows the competitive throughput of the proposed architecture even at a much lower clock frequency than those of the GPU and the CPU.Abstract:
This work presents a new flexible parameterizable architecture for image and video processing with reduced latency and memory requirements, supporting a variable input resolution. The proposed architecture is optimized for feature detection, more specifically, the Canny edge detector and the Harris corner detector. The architecture contains neighborhood extractors and threshold operators that can be parameterized at runtime. Also, algorithm simplifications are employed to reduce mathematical complexity, memory requirements, and latency without losing reliability. Furthermore, we present the proposed architecture implementation on an FPGA-based platform and its analogous optimized implementation on a GPU-based architecture for comparison. A performance analysis of the FPGA and the GPU implementations, and an extra CPU reference implementation, shows the competitive throughput of the proposed architecture even at a much lower clock frequency than those of the GPU and the CPU. Also, the results show a clear advantage of the proposed architecture in terms of power consumption and maintain a reliable performance with noisy images, low latency and memory requirements.read more
Citations
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Journal ArticleDOI
Energy Efficient Canny Edge Detector for Advanced Mobile Vision Applications
TL;DR: An energy-efficient architecture of the Canny edge detector for advanced mobile vision applications by exploiting the rank characteristic of the convolution kernel of Gaussian smoothing and Sobel gradient filters to reduce the number of additions and multiplications is presented.
Journal ArticleDOI
A systematic literature review on hardware implementation of artificial intelligence algorithms
TL;DR: This work presents a systematic literature review that focuses on exploring the available hardware accelerators for the AI and ML tools, using FPGAs, GPUs and ASICs to accelerate computationally intensive tasks.
Journal ArticleDOI
Real-time motion tracking using optical flow on multiple GPUs
TL;DR: This paper presents software that implements optical flow motion tracking using the Lucas-Kanade algorithm that is immensely fast, allowing for real-time motion tracking on videos in Full HD or even 4K format and also supports multiple GPU systems, where it scales up very well.
Proceedings ArticleDOI
An FPGA sliding window-based architecture harris corner detector
TL;DR: This paper proposes a FPGA implementation based on sliding processing window for Harris corner algorithm that has very good performance with significant less BRAM usage with respect to other approaches.
Book ChapterDOI
Detection and Description of Image Features: An Introduction
TL;DR: This chapter presents a general and brief introduction to topics of feature extraction for a variety of application domains and provides short descriptions of the chapters included in this book volume.
References
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Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Journal ArticleDOI
Speeded-Up Robust Features (SURF)
TL;DR: A novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Book
Computer Vision: Algorithms and Applications
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI
A Survey of General-Purpose Computation on Graphics Hardware
John D. Owens,David Luebke,Naga K. Govindaraju,Mark J. Harris,Jens Krüger,Aaron Lefohn,Timothy John Purcell +6 more
TL;DR: This report describes, summarize, and analyzes the latest research in mapping general‐purpose computation to graphics hardware.