On an Improved FPGA Implementation of CNN-Based Gabor-Type Filters
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, vol.59, no.11, pp.815-819, 2012 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 59 Issue: 11
- Publication Date: 2012
- Doi Number: 10.1109/tcsii.2012.2218471
- Journal Name: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.815-819
- Yıldız Technical University Affiliated: Yes
Abstract
In this brief, the details of the architecture of a previously introduced improved field-programmable gate array implementation of the cellular neural network (CNN)-based 2-D Gabor-type filter are given, and the implementation results are discussed. The proposed architecture is suitable for real-time applications with high pixel rates. The prototype is capable of processing video streams up to a pixel rate of 373.2 megapixels per second (MP/s), including full-high-definition (HD) 1080p@60 (1080 x 1920 resolution, 60-Hz frame rate, and 124.4-MP/s visible pixel rate). This brief also contains convergence rate analysis results, along with some discussions on FIR and CNN-based implementation methods.