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Open AccessArticle

Hardware Friendly Robust Synthetic Basis Feature Descriptor

1
School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
2
Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT 84602, USA
3
Cubiscan, Inc., Farmington, UT 84025, USA
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(8), 847; https://doi.org/10.3390/electronics8080847
Received: 26 May 2019 / Revised: 23 July 2019 / Accepted: 29 July 2019 / Published: 30 July 2019
(This article belongs to the Section Computer Science & Engineering)
Finding corresponding image features between two images is often the first step for many computer vision algorithms. This paper introduces an improved synthetic basis feature descriptor algorithm that describes and compares image features in an efficient and discrete manner with rotation and scale invariance. It works by performing a number of similarity tests between the feature region surrounding the feature point and a predetermined number of synthetic basis images to generate a feature descriptor that uniquely describes the feature region. Features in two images are matched by comparing their descriptors. By only storing the similarity of the feature region to each synthetic basis image, the overall storage size is greatly reduced. In short, this new binary feature descriptor is designed to provide high feature matching accuracy with computational simplicity, relatively low resource usage, and a hardware friendly design for real-time vision applications. Experimental results show that our algorithm produces higher precision rates and larger number of correct matches than the original version and other mainstream algorithms and is a good alternative for common computer vision applications. Two applications that often have to cope with scaling and rotation variations are included in this work to demonstrate its performance. View Full-Text
Keywords: feature detection; feature descriptor; synthetic basis functions; feature matching; image correspondence feature detection; feature descriptor; synthetic basis functions; feature matching; image correspondence
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Zhang, D.; Raven, L.A.; Lee, D.-J.; Yu, M.; Desai, A. Hardware Friendly Robust Synthetic Basis Feature Descriptor. Electronics 2019, 8, 847.

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