Abstract

Binary descriptors have been shown to be faster than nonbinary descriptors while producing comparable results in image matching applications. In recent years, there have been many attempts to design hardware accelerators for extraction of binary descriptors to achieve higher processing rates. One of the well-known methods is the binary robust invariant scalable key point (BRISK) algorithm, which has shown outstanding results in various applications. In this work, we propose a multiscale field-programmable gate array (FPGA)-based hardware architecture for the BRISK descriptor. In addition, a new image sampling pattern for the BRISK algorithm is described which is shown to be more efficient than the original sampling pattern for hardware implementation. Our new sampling pattern decreases the size of the patches containing the key point to one-quarter of the size of that used in the original BRISK algorithm, which leads to a reduction in FPGA resource utilization while maintaining the accuracy of the image matching application. Our proposed design is fully pipelined and achieves a frame rate of 78 fps on images with full HD resolution.

Highlights

  • Since the focus of our work is on the description portion of the binary robust invariant scalable key point (BRISK) algorithm, we briefly introduce the description process of BRISK

  • We introduce an innovative hardware-aware sampling pattern which is designed based on minimization of hardware resources, which facilitates the implementation of the BRISK algorithm for multiple scales

  • We focused on the BRISK algorithm, the idea of using a hardware-aware sampling pattern that facilitates hardware implementation could be adapted to other binary descriptors as well

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Summary

INTRODUCTION

Key point detection is the process of finding the location of key points (or interest points), which are the points in the image such as corner features that represent important information. Extracting features from a patch (a small window of image which is being processed by the descriptor) around the key point is called key point description. Features are any information from the patch that can be used for specifying each key point individually. There are many feature detection and description algorithms proposed in the literature. Binary descriptors are commonly based on the comparison of the intensity of different pairs of pixels in a patch around a key point. The main advantage of binary feature descriptors over nonbinary ones is faster computation while maintaining comparable accuracy

Hardware Implementation of Descriptors
BRISK Algorithm
New Approaches to Enhance Acceleration
Organization of this Article
Comparison of Binary Descriptor Algorithms
FPGA-Based Implementations of Binary Descriptors
FPGA-Based Implementations of BRISK Descriptor
HARDWARE-AWARE SAMPLING PATTERN FOR BRISK
HARDWARE IMPLEMENTATION OF THE MULTISCALE BRISK ALGORITHM
BRISK Pipeline
Multiscale BRISK
Assessment of the New Sampling Pattern
Effect of Clock Gating
Sharing the Multiplication Stage
Accuracy Evaluation
Discussion
CONCLUSION
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