• Title/Summary/Keyword: and Improved bit-by-bit binary tree algorithm

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Performance Analysis of Tag Identification Algorithm in RFID System (RFID 시스템에서의 태그 인식 알고리즘 성능분석)

  • Choi Ho-Seung;Kim Jae-Hyun
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.42 no.5 s.335
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    • pp.47-54
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    • 2005
  • This paper proposes and analyzes a Tag Anti-collision algorithm in RFID system. We mathematically compare the performance of the proposed algorithm with existing binary algorithms(binary search algorithm, slotted binary tree algorithm using time slot, and bit-by-bit binary tree algorithm proposed by Auto-ID center). We also validated analytic results using OPNET simulation. Based on analytic result, comparing the proposed Improved bit-by-bit binary tree algerian with bit-by-bit binary tree algorithm which is the best of existing algorithms, the performance of Improved bit-by-bit binary tree algorithm is about $304\%$ higher when the number of tags is 20, and $839\%$ higher when the number of tags is 200.

An Improvement of Bin-slotted Anti-collision Algorithm for Ubiquitous ID System

  • Kim Ji-Yoon;Kang Bong-Soo;Yang Doo-Yeong
    • International Journal of Contents
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    • v.2 no.1
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    • pp.34-38
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    • 2006
  • In this paper, an overview of anti-collision algorithm for RFID system of a standard EPC Class1 protocol is presented, and the binslotted dynamic search algorithm (BDS) based upon the slotted ALOHA and binary tree procedure is proposed and analyzed. Also, the performance is evaluated as comparing the BDS algorithm with the standard bin-slotted algorithm (BSA) through the simulation program. The performance of the proposed BDS algorithm is improved by dynamically identifying the collided-bit position and the collided bins stored in the stack of the reader. As the results, the number of request command that a reader send to tags in the reader s interrogation zone and the total recognition time are decreased to 59% as compared with BSA algorithm. Therefore, the tag identification performance is fairly improved by resolving a collision problem using the proposed BDS algorithm.

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A Semi-blind Digital Watermarking Scheme Based on the Triplet of Significant Wavelet Coefficients

  • Chu, Hyung-Suk;Batgerel, Ariunzaya;An, Chong-Koo
    • Journal of Electrical Engineering and Technology
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    • v.4 no.4
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    • pp.552-558
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    • 2009
  • We proposed a semi-blind digital image watermarking technique for copyright protection. The proposed algorithm embedded a binary sequence watermark into significant wavelet coefficients by using a quantization method. The main idea of the quantization method was to quantize a middle coefficient of the triplet of a significant wavelet coefficient according to the watermark's value. Unlike an existing algorithm, which used a random location table to find a coefficient in which the watermark bit will be embedded: the proposed algorithm used quad-tree decomposition to find a significant wavelet coefficient for embedding. For watermark detection, an original host image was not required. Thanks to the usage of significant wavelet coefficients, the proposed algorithm improved the correlation value, up to 0.43, in comparison with the existing algorithm.

An Efficient Median Filter Algorithm for Floating-point Images (부동소수점 형식 이미지를 위한 효율적인 중간값 필터 알고리즘)

  • Kim, Jin Wook
    • Journal of IKEEE
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    • v.26 no.2
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    • pp.240-248
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    • 2022
  • Floating-point images that express pixel information as real numbers are used in HDR images. There have been various researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth images and there are only a few number of algorithms applicable to floating-point images, including Gil and Werman's algorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images by improving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that the execution time is improved by about 10% compared to the Kim's algorithm by reducing the redundant work for the repetitively used binary search tree and applying the inverted index.