Robot vision application on embedded vision implementation with digital signal processor

• Published in: International journal of advanced robotic systems Vol. 17; no. 1
• Main Authors: Guan, Xiaochun, Huang, Jianlin, Tang, Tinglong
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2020; Sage Publications Ltd; SAGE Publishing
• Subjects: Algorithms; Artificial neural networks; Digital signal processors; Embedded systems; Face recognition; Handwriting recognition; Machine learning; Machine vision; Microprocessors; Neural networks; Robots; Signal processing; Vision systems; handwritten digit recognition; LeNet-5; Embedded vision; machine learning; TMS320C6748
• ISSN: 1729-8814; 1729-8806; 1729-8814
• DOI: 10.1177/1729881419900437

The great development of robot vision represented by deep learning places urgent demands on embedded vision implementation. This article introduces a hardware framework for implementation of embedded vision based on digital signal processor, which can be widely used in robot vision applications. Firstly, the article discusses implementation of a pretrained typical convolutional neural network on the digital signal processor embedded system for real-time handwritten digit recognition. Then, the article introduces the migration of OpenCV software packages to digital signal processor embedded system and the implementation flow of face detection algorithms with OpenCV on digital signal processor. The experimental results are remarkable with convolutional neural networks for handwritten digit recognition. This article provides a convenient and feasible design scheme of digital signal processor system for implementation of embedded vision.