Image Hashing based Identifier with Entropy Operator

엔트로피 연산자를 이용한 영상 해싱 기반 인식자

  • Park, Je-Ho (Dankook University, Dept. of Software Science)
  • 박제호 (단국대학교 소프트웨어학과)
  • Received : 2021.08.30
  • Accepted : 2021.09.17
  • Published : 2021.09.30

Abstract

The desire for a technology that can mechanically acquire 2D images starting with the manual method of drawing has been making possible a wide range of modern image-based technologies and applications over a period. Moreover, this trend of the utilization of image-related technology as well as image-based information is likely to continue. Naturally, as like other technology areas, the function that humans produce and utilize by using images needs to be automated by using computing-based technologies. Surprisingly, technology using images in the future will be able to discover knowledge that humans have never known before through the information-related process that enables new perception, far beyond the scope of use that human has used before. Regarding this trend, the manipulation and configuration of massively distributed image database system is strongly demanded. In this paper, we discuss image identifier production methods based on the utilization of the image hashing technique which especially puts emphasis over an entropy operator.

Keywords

References

  1. "Introduction to the Camera Obscura", Science and Media Museum. 28 Jan. 2011, Retrieved 20 Aug. 2021.
  2. Yongcheol Jeong,"The amount of the global digital data is increasing rapidly so that, 2020, the amount would reach 40ZB... it is 300 times of the amount of 2005", Digital Times, Dec. 2012.
  3. Je-Ho Park, "Still Image Identifier based over Low-frequency Area", Journal of Digital Contents Society, 11(3), pp 393-398, Sep. 2010.
  4. Je-Ho Park, Taeg Keun Whangbo, Kuinam J. Kim, "A Novel Image Identifier Generation Method Using Luminance and Location", Wireless Personal Communications, 94(1), pp 99-115, May 2017. https://doi.org/10.1007/s11277-016-3182-3
  5. Je-Ho Park, "Noble Approach of Linear Entropy based Image Identification", Journal of the Semiconductor & Display Technology, 18(3), pp 31-35, Sep. 2019.
  6. Je-Ho Park, "Multi-resolution Pyramid based Image Identification", Journal of the Semiconductor & Display Technology, 19(1), pp 6-10, Mar. 2020.
  7. Mohamed A. El-Sayed and Tarek Abd-El Hafeez, "New Edge Detection Technique based on the Shannon Entropy in Gray Level Images", Int. J. on Comput. Sci., 4, pp 186-191, 2008.
  8. Mohamed A. El-Sayed, Sayed F. Bahgat and Abdel-Khalek, "Novel Approach of Edges Detection for Digital Images Based on Hybrid Types of Entropy", Int. J. of Applied Mathematics and Information Science, pp 1809-1817, 2013.
  9. M. Kivanc Mihcak and Ramarathnam Venkatesa, "New Iterative Geometric Methods for Robust Perceptual Image Hashing", In: Sander T. (eds) Security and Privacy in Digital Rights Management, pp 13-21, 2001.
  10. Victor Zakharov et al., "Architecture of Software-Hardware Complex for Searching Images in Database". 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EICon Rus), IEEE, pp 1735-1739, 2019.