Secure video summarization framework for personalized wireless capsule endoscopy |
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| Affiliation: | 1. LAMIE Laboratory, Department of Computer Science, University of Batna 2, Algeria;2. Intelligent Media Laboratory, Department of Software, College of Software Convergence, Sejong University, Seoul, Republic of Korea;3. Digital Image Processing Laboratory, Department of Computer Science, Islamia College Peshawar, Pakistan;4. School of Data Science and Software Engineering, Qingdao University, China;1. Department of Communication Systems Engineering, Ben-Gurion University, Beer-Sheva, Israel;2. Department Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA;3. Department Electrical Engineering, Technion–Israel Institute of Technology, Haifa 32000, Israel;4. Department of Computer Science, The University of Arizona, Tucson, AZ 85721, USA;5. Department Electrical Engineering, Columbia University, New York, NY 10027, USA;7. Akamai Technologies, 150 Broadway, Cambridge, MA 02142, USA;1. School of Information Science and Technology, Northwest University, Xi’an, China;2. Naveen Jindal School of Management, University of Texas at Dallas, Richardson, TX, United States;1. Department of Computer Science, University of Illinois at Urbana–Champaign, Urbana, IL 61801, United States;2. Department of Computer Science, University of Notre Dame, Notre Dame, IN 46556, United States;3. Networked Sensing & Fusion Branch, US Army Research Laboratory, Adelphi, MD 20783, United States;4. IBM Research, Yorktown Heights, NY, United States;1. Department of Electrical & Information Engineering, Fuzhou University, Fuzhou, China;2. Department of Communication Engineering, Xiamen University, Xiamen, Fujian, China;3. Department of Electrical Engineering, National Dong Hwa University, Hualien, Taiwan;1. Ibaraki University, 4-12-1 Nakanarusawa-cho, Hitachi-shi, Ibaraki, Japan;2. National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo, Japan |
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| Abstract: | Wireless capsule endoscopy (WCE) has several benefits over traditional endoscopy such as its portability and ease of usage, particularly for remote internet of things (IoT)-assisted healthcare services. During the WCE procedure, a significant amount of redundant video data is generated, the transmission of which to healthcare centers and gastroenterologists securely for analysis is challenging as well as wastage of several resources including energy, memory, computation, and bandwidth. In addition to this, it is inherently difficult and time consuming for gastroenterologists to analyze this huge volume of gastrointestinal video data for desired contents. To surmount these issues, we propose a secure video summarization framework for outdoor patients going through WCE procedure. In the proposed system, keyframes are extracted using a light-weighted video summarization scheme, making it more suitable for WCE. Next, a cryptosystem is presented for security of extracted keyframes based on 2D Zaslavsky chaotic map. Experimental results validate the performance of the proposed cryptosystem in terms of robustness and high-level security compared to other recent image encryption schemes during dissemination of important keyframes to healthcare centers and gastroenterologists for personalized WCE. |
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| Keywords: | Information security Medical image analysis Wireless capsule endoscopy Image encryption Personalized healthcare systems Video summarization |
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