Curriculum Vitae Dr. Dimitrios K. Tzovaras



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J35] Abie, Habtamu, Bent Foyn, Jon Bing, Bernd Blobel, Peter Pharow, Jaime Delgado, Stamatis Karnouskos, Olli Pitkanen, and Dimitrios Tzovaras. "The need for a digital rights management framework for the next generation of e-government services." Electronic Government, an International Journal 1, no. 1 (2004): 8-28. (41 citations)


  1. Al-Sebie, M. (2015). Technical challenges facing integration e-government systems: an empirical study. Electronic Government, an International Journal, 11(3), 133-153.

  2. Schafer, B., Komuves, D., Zatarain, J. M. N., & Diver, L. (2015). A fourth law of robotics? Copyright and the law and ethics of machine co-production. Artificial Intelligence and Law, 23(3), 217-240.

  3. Hashemkhani Zolfani, S., Sedaghat, M., & Rad, M. D. (2014). E-government diffusion in Iran: a public sector employees’ perspective. International Journal of Business Information Systems, 15(2), 205-221.

  4. Mishra, D., & Mukhopadhyay, S. (2014). A privacy enabling content distribution framework for digital rights management. International Journal of Trust Management in Computing and Communications, 2(1), 22-39.

  5. Merhi, Mohammad I., and Kai S. Koong. "E–government effectiveness: assessment of contributing governments' ICT usage factors." International Journal of Business and Systems Research 7.1 (2013): 1-24.

  6. Drigas, Athanasios S., and Lefteris Koukianakis. "E-Government Applications for the Information Society." (2013).

  7. Merhi, M. I., & Koong, K. S. (2013). E–government effectiveness: assessment of contributing governments' ICT usage factors. International Journal of Business and Systems Research, 7(1), 1-24.

  8. Irani, Z., & Love, P. (Eds.). (2012). Evaluating information systems. Routledge.

  9. Kamal, M. M., Themistocleous, M., & Morabito, V. (2012). Evaluating e-Government infrastructure through enterprise application integration (EAI). Evaluating Information Systems, 302.

  10. Khasawneh, S., Jalghoum, Y., Harfoushi, O., & Obiedat, R. (2011). E-Government Program in Jordan: From Inception to Future Plans. International Journal of Computer Science Issues, 8(4), 568-582.

  11. Al-Sebie, M. (2011, June). The Stages of eGovernment: Correlation Between Characteristics That Affect eGovernment System. In The Proceedings of the 11th European conference on eGovernment (p. 36). Academic Pub. International.

  12. Azizan, N. (2011). Critical success factors for knowledge transfer via Australian and Malaysian Government education websites: a comparative case study.

  13. Khalil, O. E. (2011). e-Government readiness: Does national culture matter?. Government Information Quarterly, 28(3), 388-399.

  14. Sweisi, N. A. A. (2010). E-government services: an exploration of the main factors that contribute to successful implementation in Libya (Doctoral dissertation, University of Portsmouth).

  15. Li, Y., & Deng, S. L. (2009, September). Research on Automatic Government Process Remodeling in E-Government. In Management and Service Science, 2009. MASS'09. International Conference on (pp. 1-5). IEEE.

  16. McMillan, S. J. (2009). Government electronic and mobile service delivery: a success factors model (Doctoral dissertation, Victoria University).

  17. Li, Y. (2009, August). Rediscovery of government process model in e-government. In Fuzzy Systems and Knowledge Discovery, 2009. FSKD'09. Sixth International Conference on (Vol. 7, pp. 351-356). IEEE.

  18. Al-Shafi, S. (2009). Factors affecting e-Government implementation and adoption in the State of Qatar. School of Information Systems, Computing and Mathematics.

  19. Drigas, A., & Koukianakis, L. (2009). Government Online: An E-Government Platform to Improve Public Administration Operations and Services Delivery to the Citizen. Visioning and Engineering the Knowledge Society. A Web Science Perspective, 523-532.

  20. Tsai, N., Choi, B., & Perry, M. (2009). Improving the process of E-Government initiative: An in-depth case study of web-based GIS implementation.Government Information Quarterly, 26(2), 368-376.

  21. Tsai, W. H., Purbokusumo, Y., Cheng, J. M. S., & Tuan, N. D. (2009). E-government evaluation: the case of Vietnam's provincial websites. Electronic Government, An International Journal, 6(1), 41-53.

  22. Kamal, M. M., Themistocleous, M., & Morabito, V. (2009, January). Justifying the decisions for EAI adoption in LGAs: a validated proposition of factors, adoption lifecycle phases, mapping and prioritisation of factors. In System Sciences, 2009. HICSS'09. 42nd Hawaii International Conference on (pp. 1-10). IEEE.

  23. Lee, S. H., Leem, J. H. H. C. S., & Kim, B. W. (2008). u-Government Portal Evaluation: A Framework and Case Study.

  24. Kamal, M. M., Themistocleous, M., & Elliman, T. (2008). Extending IT Infastructures in the Local Government Authorities Through Enterprise Application Integration.

  25. Richards, M., Adam, K., & Price, B. A. (2008). It's Okay To Be A Dog On The Internet–Privacy And Trust In e-Government. Relation, 10(1.114), 4220.

  26. Irani, Z., & Elliman, T. (2008). Creating social entrepreneurship in local government. European Journal of Information Systems, 17(4), 336-342.

  27. Lee, H., Irani, Z., Osman, I. H., Balci, A., Ozkan, S., & Medeni, T. D. (2008). Research note: toward a reference process model for citizen-oriented evaluation of e-government services. Transforming Government: People, Process and Policy, 2(4), 297-310.

  28. Liu, C. C., & Wang, H. J. (2007). Developing measures of digital capital and virtual value chain construction in job search websites. International Journal of Management and Enterprise Development, 4(1), 66-81.

  29. Al-Mashari, M. (2007). A benchmarking study of experiences with electronic government. Benchmarking: An International Journal, 14(2), 172-185.

  30. Tahinakis, P., Mylonakis, J., & Protogeros, N. (2006). The contribution of e-government to the modernisation of the Hellenic taxation system. Electronic Government, an International Journal, 3(2), 139-157.

  31. Walsh, P. E. (2006). E-payment: Cheque 21. International Journal of Electronic Finance, 1(2), 222-240.

  32. Von Lubitz, D., & Wickramasinghe, N. (2006). Key challenges and policy implications for governments and regulators in a networkcentric healthcare environment. Electronic Government, an International Journal, 3(2), 204-224.

  33. McMahon, R. A., & Bressler, L. (2005). E-government: do audits aid the netologically disadvantaged. Electronic Government, an International Journal, 2(4), 413-425.

  34. McMahon, R. A. (2005). E-government: effects on the netologically disadvantaged. Electronic Government, an International Journal, 2(4), 460-471.

  35. Becker, S. A. (2005). Potential trust barriers in US state e-government privacy policies. Electronic Government, An International Journal, 2(3), 334-352.

  36. Al-Sebie, M., & Irani, Z. (2005). Technical and organisational challenges facing transactional e-government systems: an empirical study. Electronic Government, An International Journal, 2(3), 247-276.

  37. Belanger, F., Carter, L. D., & Schaupp, L. C. (2005). U-government: a framework for the evolution of e-government. Electronic Government, an International Journal, 2(4), 426-445.

  38. Liu, C. C. (2005). Using e-governmental indicators to build virtual value chain. Electronic Government, An International Journal, 2(3), 277-291.

  39. Adam, K., Price, B., Richards, M., & Nuseibeh, B. (2005). A privacy preference model for pervasive computing. Proceedings of the Euro mGov 2005.

  40. Al-Sebie, M., Irani, Z., & Eldabi, T. (2005). Issues relating to the transaction stage of the e-government system. Electronic Government, an International Journal, 2(4), 446-459.

  41. Nikolopoulos, K., Patrikakis, C. Z., & Lin, B. (2004). Forecasting systems for e-government. Electronic Government, an International Journal, 1(4), 374-383.

[J39] P. Daras, D. Zarpalas, A. Axenopoulos, D. Tzovaras and M. G. Strintzis: "3D Shape-Structure Comparison Method for Protein Classification", IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 3, Issue 3, pp. 193-207, July 2006. (34 citations)



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  3. Sukumar, N., et al. "Molecular Descriptors for Biological Systems."Computational Approaches in Cheminformatics and Bioinformatics (2012): 107-143.

  4. Liu, Yu-Shen, et al. "3DMolNavi: A web-based retrieval and navigation tool for flexible molecular shape comparison." BMC bioinformatics 13.1 (2012): 95.

  5. Mirceva, Georgina, et al. "Efficient Approaches for Retrieving Protein Tertiary Structures." IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 9.4 (2012): 1166-1179.

  6. Nanni, Loris, Sheryl Brahnam, and Alessandra Lumini. "Wavelet images and Chou’s pseudo amino acid composition for protein classification." Amino acids(2012): 1-9.

  7. Deformation Invariant Local Descriptors for Protein Surface Comparison, YL Tsai, HW Wang, TW Pai, WS Tzou… - Intelligent Systems and …, 2011 - actapress.com

  8. Liu, Y. S., Ramani, K., & Liu, M. (2011). Computing the inner distances of volumetric models for articulated shape description with a visibility graph. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(12), 2538-2544.

  9. Mirceva, G., & Davcev, D. (2011, September). SVM based approaches for classifying protein tertiary structures. In Data and Knowledge Engineering (ICDKE), 2011 International Conference on (pp. 1-7). IEEE.

  10. Ravichandran, L. (2011). Waveform Mapping and Time-Frequency Processing of Biological Sequences and Structures (Doctoral dissertation, ARIZONA STATE UNIVERSITY).

  11. Wang, J., Li, Y., Bai, X., Zhang, Y., Wang, C., & Tang, N. (2011). Learning context-sensitive similarity by shortest path propagation. Pattern Recognition, 44(10), 2367-2374.

  12. Wang, J., Li, Y., Zhang, Y., Tang, N., & Wang, C. (2011, May). Class conditional distance metric for 3D protein structure classification. In Bioinformatics and Biomedical Engineering,(iCBBE) 2011 5th International Conference on (pp. 1-4). IEEE.

  13. Wavelet images and Chou’s pseudo amino acid composition for protein classification, Loris Nanni, Sheryl Brahnam and Alessandra Lumini, Amino Acids, DOI: 10.1007/s00726-011-1114-

  14. Efficient Approaches for Retrieving Protein Tertiary Structures, Mirceva G, Cingovska I, Dimov Z, Davcev D., IEEE/ACM Trans Comput Biol Bioinform. 2011 Oct 17. [Epub ahead of print]

  15. Nanni, L., Shi, J. Y., Brahnam, S., & Lumini, A. (2010). Protein classification using texture descriptors extracted from the protein backbone image. Journal of Theoretical Biology, 264(3).

  16. Nanni, L., Brahnam, S., & Lumini, A. (2010). High performance set of PseAAC and sequence based descriptors for protein classification. Journal of Theoretical Biology, 266(1).

  17. Using diffusion distances for flexible molecular shape comparison, Yu-Shen Liu, Qi Li, Guo-Qin Zheng, Karthik Ramaniand William Benjamin, BMC Bioinformatics 2010, 11:480doi:10.1186/1471-2105-11-480, Published 24 September 2010

  18. A Protein Classifier Based on SVM by Using the Voxel Based Descriptor, Georgina Mirceva, Andreja Naumoski and Danco Davcev, Computer Science, Rough Sets and Current Trends in Computing, Lecture Notes in Computer Science, 2010, Volume 6086/2010, 640-648, DOI: 10.1007/978-3-642-13529-3_68

  19. Protein Classification Based on 3D Structures and Fractal Features, Georgina Mirceva, Zoran Dimov, Slobodan Kalajdziski and Danco Davcev, ICT Innovations, 2010, Part 2, 115-124, DOI: 10.1007/978-3-642-10781-8_13

  20. Paquet, E., & Viktor, H. L. (2009). Finding Protein Family Similarities in Real Time Through Multiple 3D and 2D Representations, Indexing and Exhaustive Searching. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval-(KDIR 2009) (pp. 127-133).

  21. Jian-Yu, S. B. L. N., & Lumini, S. A. Local phase quantization texture descriptor for protein classification.

  22. TRIVODALIEV, K., KALAJDZISKI, S., & DAVCEV, D. (2009). A System for Protein Classification Based on Protein 3D Structure. In proceedings of The 5th international conference SETIT (pp. 22-26).

  23. Dimov, Z., Mirceva, G., & Davcev, D. Protein distance matrices comparison using sequence alignment techniques.

  24. 2009 Seventh International Workshop on Content-Based Multimedia Indexing, C Käs, H Nicolas, KWC Domain - computer.org

  25. 3D Model Retrieval Using Probability Density-Based Shape Descriptors, Ceyhun Burak Akgu¨ l, Bu¨ lent Sankur, Yu¨ cel Yemez, and Francis Schmitt, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 31, NO. 6, JUNE 2009

  26. IDSS: deformation invariant signatures for molecular shape comparison, Yu-Shen Liu, Yi Fang and Karthik Ramani, BMC Bioinformatics 2009, 10:157 doi: 10.1186/1471-2105-10-157, May 2009

  27. Fast SCOP Classification of Structural Class and Fold Using Secondary Structure Mining in Distance Matrix, Jian-Yu Shi1, and Yan-Ning Zhang, V. Kadirkamanathan et al. (Eds.): PRIB 2009, LNBI 5780, pp. 344–353, 2009. © Springer-Verlag Berlin Heidelberg 2009

  28. Three dimensional shape comparison of flexible proteins using the local-diameter descriptor, Yi Fang, Yu-Shen Liu and Karthik Ramani, BMC Structural Biology 2009, 9:29, doi:10.1186/1472-6807-9-29, May 2009

  29. Quantitative protein descriptors for secondary structure characterization and protein classification, Anton Lindström, Fredrik Pettersson and Anna Linusson, Chemometrics and Intelligent Laboratory Systems, Volume 95, Issue 1, 15 January 2009, Pages 74-85

  30. SGNG Protein Classifier by Matching 3D Structures, Georgina Mirceva, Andrea Kulakov, and Danco Davcev, E. Corchado et al. (Eds.): HAIS 2009, LNAI 5572, pp. 425–432, 2009. c_ Springer-Verlag Berlin Heidelberg 2009

  31. Capri/MR: Exploring Protein Databases from a Structural and Physicochemical Point of View, Eric Paquet, Herma L.Victor, Proceedings of the VLDB Endowment, Volume 1 ,  Issue 2  (August 2008) SESSION: Demonstrations: tuning, systems optimization, Pages 1504-1507  

  32. Feature Selection and Combination Criteria for Improving Accuracy in Protein Structure Prediction, Lin, K.-L.; Chun-Yuan Lin; Chuen-Der Huang; Hsiu-Ming Chang; Chiao-Yun Yang; Chin-Teng Lin; Chuan Yi Tang; Hsu, D.F.; NanoBioscience, IEEE Transactions on, Volume 6,  Issue 2,  June 2007 Page(s):186 – 196

  33. SHREC’07 - Protein Retrieval Challenge, Maja Temerinac, Marco Reisert and Hans Burkhardt, Proceedings of Shape Modelling, 2007

  34. Protein Classification by Matching 3D Structures, Slobodan Kalajdziski , Georgina Mirceva , Kire Trivodaliev , Danco Davcev, 2007 Frontiers in the Convergence of Bioscience and Information Technologies, Jeju Island, Korea , October 11-October 13, ISBN: 978-0-7695-2999-8

[J46] Dimosthenis Ioannidis, Dimitrios Tzovaras, Ioannis G. Damousis, Savvas Argyropoulos, and Konstantinos Moustakas, "Gait Recognition using Compact Feature Extraction Transforms and Depth Information", IEEE Transactions on Information Forensics and Security, Volume: 2,  Issue: 3, Part 2, pp. 623-630, Sept 2007. (29 citations)




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  6. Igual, Laura, Àgata Lapedriza, and Ricard Borràs. "Robust gait-based gender classification using depth cameras." EURASIP Journal on Image and Video Processing 2013.1 (2013): 1.

  7. Huang, Xiaxi, and Nikolaos V. Boulgouris. "Gait Recognition With Shifted Energy Image and Structural Feature Extraction." Image Processing, IEEE Transactions on 21.4 (2012): 2256-2268.

  8. Kusakunniran, Worapan, et al. "Gait recognition under various viewing angles based on correlated motion regression." Circuits and Systems for Video Technology, IEEE Transactions on 22.6 (2012): 966-980.

  9. Kusakunniran, Worapan, et al. "Cross-view and multi-view gait recognitions based on view transformation model using multi-layer perceptron." Pattern Recognition Letters 33.7 (2012): 882-889.

  10. Das Choudhury, Sruti, and Tardi Tjahjadi. "Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors." Pattern Recognition (2012).

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  12. Shukla, Richa, et al. "Gender Identification in Human Gait Using Neural Network." International Journal of Modern Education and Computer Science (IJMECS) 4.11 (2012): 70.

  13. McGuire, Michael L. "An Overview of Gait Analysis and Step Detection in Mobile Computing Devices." Intelligent Networking and Collaborative Systems (INCoS), 2012 4th International Conference on. IEEE, 2012.

  14. Manabe, Yusuke, Ryuki Saito, and Kenji Sugawara. "Biometric gait verification by horizontal swings in frontal manner towards human-aware environment."Cognitive Informatics & Cognitive Computing (ICCI* CC), 2012 IEEE 11th International Conference on. IEEE, 2012.

  15. Sivapalan, S., Chen, D., Denman, S., Sridharan, S., & Fookes, C. (2011, October). Gait energy volumes and frontal gait recognition using depth images. In Biometrics (IJCB), 2011 International Joint Conference on (pp. 1-6). IEEE.

  16. Cross-view and multi-view gait recognitions based on view transformation model using multi-layer perceptron, Worapan Kusakunniran, Qiang Wu, Jian Zhang, Hongdong Li, Pattern Recognition Letters, In Press, Corrected Proof - Note to users , 27 April 2011

  17. Lu, J., & Tan, Y. P. (2010). Gait-based human age estimation. Information Forensics and Security, IEEE Transactions on, 5(4), 761-770.

  18. Setti, F. (2010). Metodi e applicazioni di sensor fusion per i sistemi meccatronici.

  19. Automatic Gait Recognition Using Kernel Principal Component Analysis, Xiang-tao Chen, Zhi-hui Fan, Hui Wang, Zhe-qing Li, Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on , Issue Date: 23-25 April 2010, On page(s): 1 - 4 , Location: Wuhan

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  22. Action Recognition in Video by Covariance Matching of Silhouette Tunnels, Kai Guo, Prakash Ishwar, and Janusz Konrad, Proc. of 22-nd Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI-2009, Oct. 11–14, 2009, Rio de Janeiro, Brazil

  23. Gait Representation and Recognition Using Haar Wavelet and Radon Transform, hijing Liu, 2009 WASE International conference on Information Engineering, Taiyuan, Shanxi, china, 10-11 July 2009

  24. Computational Intelligence in Gait Research: A Perspective on Current Applications and Future Challenges, Daniel T. H. Lai, Rezaul K. Begg, and Marimuthu Palaniswami, IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 13, NO. 5, SEPTEMBER 2009

  25. Biometric Gait Recognition with Carying and clothing Variants, Shamsher Singh and K.K. Biswas, S.Chaudhury et al. (Eds. ): PReMI2009, LNCS 5909, pp.446-451, 2009, Springer-Verlag Berlin Heidelberg 2009

  26. J.-F. Hu, X.-C. Bao, “Person identification based on electroencephalogram signals”, Journal of Clinical Rehabilitative Tissue Engineering Research 13 (17), pp. 3260-3264, 2009.

  27. Z.-J. Xue, B.-K. Wan, X.-H. Liu, D. Ming, S.-J. Jin, “A new technique of gait feature extraction based on multi-parameter model”, Chinese Journal of Biomedical Engineering 28 (1), pp. 22-26, 2009.

  28. J. Hu, P. Xuecai, “EEG identity authentication method”, Chinese tissue engineering research and clinical rehabilitation, no. 17, 2009, pp. 3260-3264.

  29. C. Xue, Y Baeg, H. Liu Hui, S. Jin, “Multi-parameters gait model extraction”, The Chinese Journal of biomedical engineering, 2009 Cap.28 volume 1, pp. 22-26.

[J38] P. Daras, D. Zarpalas, D.Tzovaras and M.G.Strintzis: "Efficient 3D Model Search and Retrieval Using Generalized 3D Radon Transforms", IEEE Trans. on Multimedia,Volume 8, Issue 1,  Feb. 2006 Page(s):101-114. (27 citations)




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  3. Kien, Dang Trung. "Semi-Interactive Construction of 3D Event Logs for Scene Investigation." (2013).

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  8. Philipp-Foliguet, Sylvie, et al. "Artwork 3D model database indexing and classification." Pattern Recognition 44.3 (2011): 588-597.

  9. Sfikas, Konstantinos, Theoharis Theoharis, and Ioannis Pratikakis. "ROSy+: 3D object pose normalization based on pca and reflective object symmetry with application in 3D object retrieval." International Journal of Computer Vision 91.3 (2011): 262-279.

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  22. PANORAMA: A 3D Shape Descriptor Based on Panoramic Views for Unsupervised 3D Object Retrieval, Panagiotis Papadakis · Ioannis Pratikakis ·Theoharis Theoharis · Stavros Perantonis, Int J Comput Vis DOI 10.1007/s11263-009-0281-6, 22 July 2009, © Springer Science+Business Media, LLC 2009

  23. Efficient 3D shape matching and retrieval using a concrete radialized spherical projection representation, Panagiotis Papadakis, Ioannis Pratikakis, Stavros Perantonis and Theoharis Theoharis, Pattern Recognition, Volume 40, Issue 9, September 2007, Pages 2437-2452

  24. Support Vector Machine active learning for 3D model retrieval, LENG Biao, QIN Zheng, LI Li-qun, Journal of Zhejiang University - Science A, Volume 8, Number 12 / November, 2007, pp.1953-1961

  25. DEALING WITH DEGENERATE INPUT IN 3D MODELING OF INDOOR SCENES USING HANDHELD CAMERAS, T.K. Dang and M. Worring, Multimedia and Expo, 2007 IEEE International Conference on, Publication Date: 2-5 July 2007, On page(s): 108-111

  26. Support Vector Machine active learning for 3D model retrieval, LENG Biao, QIN Zheng, LI Li-qun, Journal of Zhejiang University SCIENCE A, ISSN 1673-565X(Print), 1862-1775(Online), Monthly, 2007   Vol. 8   No. 12   p. 1953~1961

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[J54] Ioannis G. Damousis, Dimitrios Tzovaras and Angelos Bekiaris, “Unobtrusive multimodal biometric authentication – The HUMABIO Project concept”, EURASIP Journal on Advances in Signal Processing, vol. 2008, Article ID 265767, 11 pages, 2008. doi:10.1155/2008/265767. (26 citations)




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  1. Zhu, L., Zhang, P., Li, D., Zhu, X., & Wang, C. (2015). A novel change detection method based on high-resolution SAR images for river course. Optik-International Journal for Light and Electron Optics, 126(23), 3659-3668.



  3. Kathirvalavakumar, T., and E. Ponmalar. "Self organizing map and wavelet based image compression." International Journal of Machine Learning and Cybernetics (2012): 1-8.

  4. Image Processing Apparatus and Method, Tamotsu Kajihara, United States Patent, Patent No.:US7,366,350B2, April 29, 2008.

  5. Xuli Shi, Zhaoyang Zhang, Liquan Shen, Yu Lu and Suxing Liu, “Multiresolution segmentation of video objects in the compression domain” Optical Engineering, Volume 46, Issue 9, September 2007

  6. Jiang, J.   Feng, G.   Yin, Y.  , “Progressive content access to databases of JPEG-compressed images”, Image Processing IET, Volume: 1,  Issue: 2, pp 207-214, June 2007

  7. Jose A. Garcia, Rosa Rodriguez-Sánchez, and Joaquín Fdez-Valdivia, “Optimal exploratory effort to build knowledge for video transmission”, Optical Engineering, Volume 46, Issue 4, April 2007

  8. Yuan He, Yupin Luo and Dongcheng Hu, “Automatic seeded region growing based on gradient vector flow for color image segmentation”, Optical Engineering, Volume 46, Issue 4, April 2007

  9. Juan José de Dios, “Skin color and feature-based segmentation for face localization”, Optical Engineering, Volume 46, Issue 3, March 2007

  10. Zhi Liu, Zhaoyang Zhang, Liquan Shen, “Moving object segmentation in the H.264 compressed domain”, Optical Engineering, Volume 46, Issue 1, January 2007

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  19. Angiocardiographic digital still images compressed via irreversible methods: concepts and experiments, Luisa Portonia, , Carlo Combib, Giuseppe Pozzic, Francesco Pincirolia, d, Johannes Peter Fritsche and Rüdiger Brenneckee, International Journal of Medical Informatics, Volume 46, Issue 3, October 1997, Pages 185-204



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