Author:
Chiranjeevi G.N.,Kulkarni Subhash
Abstract
The overwhelming majority of image processing algorithms are two-dimensional (2D) and, as a result, their scope is limited. As a result, the 2D convolution function has important implications for image processing needs. The 2D convolution and MAC design processes are used to perform image analysis tasks such as image blurring, softening, feature extraction, and image classification. This study’s primary goal is to develop a more efficient MAC control block-based architectural style for two-dimensional convolutions. In image processing applications, convolution deployment, the recommended 2D convolution architectural methodology, is significantly faster and requires far fewer hardware resources. The resulting convolution values are stored in memory when the convolution procedure is completed.
Reference25 articles.
1. Smith TF, Waterman MS. Identification of common molecular subsequence’s. Journal of Molecular Biology. 1981;147:195-197
2. Nikhil R. Blue spec System Verilog: Efficient, correct RTL from high level specifications. In: Proceedings of the Second ACM and IEEE International Conference on Formal Methods and Models for Co-Design (MEMOCODE’04). CA, USA, San Diego. 23-25 June 2004. pp. 69-70
3. Shoup R. Parameterized Convolution Filtering in a Field Programmable Gate Array Interval. Technical Report. Palo Alto, California; 1993
4. Neoh HS, Hazanchuk A. Adaptive edge detection for real-time video processing using FPGAs. In: 2004 GSPx Conference. 2004
5. Wang J, Zhong S, Yan L, Cao Z. An embedded system-on-chip architecture for real-time visual detection and matching. IEEE Transactions on Circuits and Systems for Video Technology. 2014;24:525-538
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