Browse > Article
http://dx.doi.org/10.22156/CS4SMB.2019.9.3.008

Enhanced Local Directional Pattern based video shot boundary detection and automatic synchronization for STB quality inspection  

Cho, Youngtak (Dept. of Computer Science and Engineering, Kyung Hee University)
Chae, Oksam (Dept. of Computer Science and Engineering, Kyung Hee University)
Publication Information
Journal of Convergence for Information Technology / v.9, no.3, 2019 , pp. 8-15 More about this Journal
Abstract
Recently, the importance of pre-shipment quality inspection has been emphasized due to the increase of STB supply. In this paper, we propose a method to support automation of quality inspection through simultaneous multi-channel input of STB video signal. The proposed method extracts a fingerprint using the center scan line of the image after stable video shot boundary detection using CeLDP combining color information and LDP code and performs synchronization between input video channels. The proposed method shows stronger shot boundary detection performance than the conventional shot detection method. Through the experiments applied to the real environment, it is possible to secure reliability and real-time quality check for synchronization between multi-channel inputs required for STB quality inspection. Also, based on the proposed method, we intend to study a large-scale quality inspection method in the future and propose a more effective quality inspection system.
Keywords
STB QC; Shot Detection; LDP; Video Fingerprint; Automatic Video Synchronization;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 stb-tester. Automated Testing for Set-Top Boxes and Smart TVs, http://Stb-tester.com [Accessed 18 Jan. 2019].
2 J. S. Boreczky & L. A. Rowe. (1996). Comparison of video shot boundary detection techniques. Journal of Electronic Imaging, 5(2), 122-128.   DOI
3 J. Mas & G. Fernandez. (2003). Video shot boundary detection based on color histogram. Notebook Papers TRECVID2003, Gaithersburg, Maryland, NIST.
4 A. Nagasaka & Y. Tanaka. (1992). Automatic video indexing and full-video search for object appearances. Journal of Information Processing, 15(2), 316.
5 K. O. Ahn, et al. (2015). Video Shot Boundary Detection based on Color and LBP code for Remote Smart Collaboration. IEEK summer conference, pp. 593-596.
6 T. Ahonen, A. Hadid & M. Pietikainen. (2006). Face description with local binary patterns: Application to face recognition. IEEE transactions on Pattern Analysis and Machine Intelligence, 28(12), 2037-2041.   DOI
7 T. Jabid, M. H. Kabir & O. S. Chae. (2010, Aug). Local directional pattern (LDP)-A robust image descriptor for object recognition. In Advanced Video and Signal Based Surveillance (AVSS), 2010 Seventh IEEE International Conference on, 482-487.
8 S. I. Lee & C. D. Yoo. (2008). Robust video fingerprinting for content-based video identification. IEEE Transactions on Circuits and Systems for Video Technology, 18(7), 983-988.   DOI
9 J. Song, Y. Yang, Z. Huang, H. Shen & J. Luo. (2013). Effective multiple feature hashing for largescale near-duplicate video retrieval. IEEE Transactions on Multimedia, 15(8), 1997-2008.   DOI
10 D. H. Kim & Y. Kim. (2018, Feb). A New Exploratory Testing Method for Improving the Effective IP Set-Top Box Test. Journal of The Korea Society of Computer and Information, 23(2), 9-16.   DOI
11 H. J. Jung. (2017). The Quantity Data Estimation for Software Quality Testing. Journal of the Korea Convergence Society, 8(10), 37-43.   DOI
12 X. Lv & Z. J. Wang. (2013). Compressed binary image hashes based on semisupervised spectral embedding. IEEE Transactions on Information Forensics and Security, 8(11), 1838-1849.   DOI
13 S. C. Hwang. (2014). Development of Video Watermark System for Low-specification System as Android Platforms. Journal of The Korea Society of Computer and Information, 19(7), 141-149.   DOI
14 M. Li & V. Monga. (2014). Twofold video hashing with automatic synchronization. 2014 IEEE International Conference on Image Processing (ICIP), 5362-5366.
15 ITU. (2011). Recommendation ITU-R BT.601-7, Studio encoding parameters of digital television for standard 4: 3 and wide-screen 16: 9 aspect ratios.
16 Y. Benjamini, & Y. Hochberg. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1), 289-300.   DOI
17 S. Y. Min, S. H. Park & N. H. Lee. (2011). SW Quality of Convergence Product: Characteristics, Improvement Strategies and Alternatives. Journal of Convergence for Information Technology, 1(1), 19-28.
18 D. H. Kim, Y. J. Jung & J. E. Hong. (2016). Analysis of Refactoring Techniques and Tools for Source Code Quality Improvement. Journal of Convergence for Information Technology, 6(4), 137-150.   DOI
19 D. H. Byun. (2012). Methodology for Measuring the Quality of Three-Dimensional Television. Journal of Digital Convergence, 10(4), 1-9.   DOI
20 Tae-Kyung Cho. (2015). The Study on the Performance Evaluation of IPTV according to the increase of network traffic on the Internet Environment. Journal of Digital Convergence, 13(11), 179-185.   DOI
21 J. Bach. (2004). Exploratory testing. The testing practitioner, 253-265.