Title
A Programmable CNN Architecture and Its Hardware-Software Co-design Approach for Image Processing and Stimulating Visual Illusions
Abstract
Cellular neural network (CNN) shows a strong resemblance to biological visual system, and has found numerous applications in image and video signal processing, and in artificial intelligence. In this paper, a programmable architecture based on simplicial CNN is proposed for image processing operations. The proposed architecture provides a flexible and reconfigurable hardware platform that can be used to implement gray-level and binary image processing functions. Hardware-software co-design approach is applied to further improve its efficiency and completeness. Experimental results show that several common image processing tasks are fully completed by using a combination of the basic instructions. Additionally, studying on visual illusion is regarded as that it can provide fundamental insights for biological perception and cognition. It is also shown in the experimental results that the proposed model is responsible for stimulating visual illusions.
Year
DOI
Venue
2016
10.1109/QRS-C.2016.59
2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
Keywords
Field
DocType
Cellular neural network,image processing,visual illusion,hardware-software co-design
Computer vision,Signal processing,Optical illusion,Computer science,Human visual system model,Binary image,Image processing,Artificial intelligence,Digital image processing,Cellular neural network,Reconfigurable computing
Conference
ISBN
Citations 
PageRank 
978-1-5090-3714-8
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Jianwei Zheng111.37
Chunhang Xu200.34
Donghui Guo310721.93