Browse > Article
http://dx.doi.org/10.7471/ikeee.2022.26.2.226

Hardware Architecture for Entropy Filter Implementation  

Sim, Hwi-Bo (Dept. of Electronics Engineering, Dong-A University)
Kang, Bong-Soon (Dept. of Electronics Engineering, Dong-A University)
Publication Information
Journal of IKEEE / v.26, no.2, 2022 , pp. 226-231 More about this Journal
Abstract
The concept of information entropy has been widely applied in various fields. Recently, in the field of image processing, many technologies applying the concept of information entropy have been developed. As the importance and demand of computer vision technologies increase in modern industry, real-time processing must be possible in order for image processing technologies to be efficiently applied to modern industries. Extracting the entropy value of an image is difficult to process in real-time due to the complexity of computation in software, and a hardware structure of an image entropy filter capable of real-time processing has never been proposed. In this paper, we propose for the first time a hardware structure of a histogram-based entropy filter that can be processed in real time using a barrel shifter. The proposed hardware was designed using Verilog HDL, and Xilinx's xczu7ev-2ffvc1156 was set as the target device and FPGA was implemented. As a result of logic synthesis using the Xilinx Vivado program, it has a maximum operating frequency of 750.751 MHz in a 4K UHD high-resolution environment, and it processes more than 30 images per second and satisfies the real-time processing standard.
Keywords
Entropy Filter; Histogram; Barrel Shifter; 4K UHD; Real time processing; Hardware implementation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 A. K. Singh, H. P. Singh and Karmeshu, "Analysis of Finite Buffer Queue: Maximum Entropy Probability Distribution With Shifted Fractional Geometric and Arithmetic Means," in IEEE Communications Letters, vol.19, no.2, pp. 163-166, 2015. DOI: 10.1109/LCOMM.2014.2377236   DOI
2 H. Li, W. Du, K. Fan, J. Ma, K. Ivanov and L. Wang, "The Effectiveness Assessment of Massage Therapy Using Entropy-Based EEG Features Among Lumbar Disc Herniation Patients Comparing With Healthy Controls," in IEEE Access, vol.8, pp.7758-7775, 2020. DOI: 10.1109/ACCESS.2020.2964050   DOI
3 J. Prakash, S. Mandal, D. Razansky and V. Ntziachristos, "Maximum Entropy Based Non-Negative Optoacoustic Tomographic Image Reconstruction," in IEEE Transactions on Biomedical Engineering, vol.66, no.9, pp.2604-2616, 2019. DOI: 10.1109/TBME.2019.2892842   DOI
4 Baljit Singh, Amar Partap Singh, "Edge Detection in Gray Level Images based on the Shannon Entropy," Journal of Computer Science, Vol.4, No.3, pp.186-191, 2008. DOI: 10.3844/jcssp.2008.186.191   DOI
5 S. A. Fahmy, P. Y. K. Cheung and W. Luk, "Novel FPGA-based implementation of median and weighted median filters for image processing," International Conference on Field Programmable Logic and Applications, pp.142-147, 2005. DOI: 10.1109/FPL.2005.1515713   DOI
6 G. Chen and B. Wen, "An Improved Image Entropy Algorithm Suitable for Digital Painting Style," 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), pp.1742-1746, 2020. DOI: 10.1109/ICMCCE51767.2020.00382   DOI
7 J. Zhang, Y. Liu and H. Xing, "Application of Improved 2-D Entropy Algorithm in Rubber Tree Image Segmentation," 2019 2nd International Conference on Safety Produce Informatization (IICSPI), pp.311-314, 2019. DOI: 10.1109/IICSPI48186.2019.9096014   DOI
8 F. Hrzic, V. Jansky, D. Susanj, G. Gulan, I. Kozar and D. Z. Jericevic, "Information entropy measures and clustering improve edge detection in medical X-ray images," 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp.0164-0166, 2018. DOI: 10.23919/MIPRO.2018.8400032   DOI
9 S. Sankaran and G. Sethumadhavan, "Entropy-Based Colour Splitting in Dermoscopy Images to Identify Internal Borders," 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), pp.771-774, 2018. DOI: 10.1109/ICIRCA.2018.8597177   DOI
10 Y. Zou, J. Zhang, M. Upadhyay, S. Sun and T. Jiang, "Automatic Image Thresholding Based on Shannon Entropy Difference and Dynamic Synergic Entropy," in IEEE Access, vol.8, pp.171218-171239, 2020. DOI: 10.1109/ACCESS.2020.3024718   DOI
11 T. Lan, Z. Cai and B. Ye, "Modeling of Lunar Digital Terrain Entropy and Terrain Entropy Distribution Model," in IEEE Transactions on Geoscience and Remote Sensing, vol.59, no.2, pp.1052-1066, 2021. DOI: 10.1109/TGRS.2020.2999582   DOI
12 S. M. Lee, and B. S. Kang, "Hardware Implementation of Minimum Filter based on 2-D Cumulative Histogram", ISOCC, pp.297-298, 2019.