Radha, Prakhar, Shaik, Shantanu, and Veena. International Journal of Innovative Research in Information Security, 09 (2):
28-38(May 2023)1 M. Fernando and J. Wijayanayaka, "Low cost approach for real time sign language recognition," 2013 IEEE 8th International Conference on Industrial and Information Systems, 2013, pp. 637-642, https://doi.org/10.1109/iciinfs.2013.6732059 2 M. Z. Islam, M. S. Hossain, R. ul Islam and K. Andersson, "Static Hand Gesture Recognition using Convolutional Neural Network with Data Augmentation," 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2019, pp. 324-329, https://doi.org/10.1109/iciev.2019.8858563 3 E. Kaya and T. Kumbasar, "Hand Gesture Recognition Systems with the Wearable Myo Armband," 2018 6th International Conference on Control Engineering & Information Technology (CEIT), 2018, pp. 1-6, https://doi.org/10.1109/ceit.2018.8751927 4 Lesha Bhansali and Meera Narvekar. Gesture Recognition to Make Umpire Decisions. International Journal of Computer Applications 148(14):26-29, August 2016. https://doi.org/10.5120/ijca2016911312 5 Suvarna Nandyal and Suvarna Laxmikant Kattimani 2021 J. Phys.: Conf. Ser. 2070 012148 6 Y. Madhuri, G. Anitha. and M. Anburajan., "Vision- based sign language translation device," 2013 International Conference on Information Communication and Embedded Systems (ICICES), 2013, pp. 565-568, https://doi.org/10.1109/icices.2013.6508395 7 Nusirwan Anwar bin Abdul Rahman, Kit Chong Wei and John See Faculty of Information Technology, Multimedia University. 8 Moin, A., Zhou, A., Rahimi, A. et al. A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition. Nat Electron 4, 54–63 (2021). https://doi.org/10.1038/s41928-020-00510-8 9 Ravi, H. Venugopal, S. Paul and H. R. Tizhoosh, Ä Dataset and Preliminary Results for Umpire Pose Detection Using SVM Classification of Deep Features," 2018 IEEE SymposiumSeries on Computational Intelligence (SSCI), 2018, pp. 1396-1402, https://doi.org/10.1109/ssci.2018.8628877 10 M. A. Shahjalal, Z. Ahmad, R. Rayan and L. Alam, Än approach to automate the scorecard in cricket with computer vision and machine learning," 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), 2017, pp. 1-6, https://doi.org/10.1109/eict.2017.8275204.
Krithika, Lakshitha, Monica, Priya, and Veena. International Journal of Innovative Research in Information Security, 09 (2):
21-27(May 2023)1. Currency Recognition system using Image Processing. SANDEEP KUMAR CHAUBEY Andrew S. Morgan Kaufmann Publishers, 1995. 2. A Survey on Indian Currency Note Denomination Recognition System. Aruna Manpreet Bagga, Dr.Baljit Singh. 1995. 3. Dr. Baljith Singh, Aruna D H Indian currency note denomination system. 4. Ms. Monali Patil, Prof. Jayant Adhikari Detection of fake currency using digital image processing. 5. Arun Anoop M, Dr K.E. Kannammal Fake currency detection 6. Vidhi Roy and Sushanth Patil Fake Currency detection using image processing. 7. M. Deborah and Soniya Prathap Detection of Fake currency using edge detection. 8. Akash Rana, Avinash Kumar and Shivam Kumar Jha Detection of fake currency using machine learning technique. 9. Mayadevi, A. Gaikwad, Vaijinath, V. Bhosle and Vaibhav Currency note feature extraction. 10. Brinda M Object Detection using Haar-Like Feature Extraction..
Dhanalakshmi, Jayasurya, Manoj, and Manu. International Journal of Innovative Research in Information Security, 9 (2):
15-20(May 2023)1 D. Pavithra; Ranjith Balakrishnan, “IOT based monitoring and control system for home automation”, IEEE Explore, Communication Technologies (GCCT). https://doi.org/10.1109/gcct.2015.7342646 2 Dr. M. Suresh, A. Amulya, M. Hari Chandana, P. Amani, T. Lakshmi Prakasam. “Anti theft flooring system using raspberry pi using” in Compliance Engineering journal, vol 12, no. 7, pp. 306 – 317, 2021. 3 Sonali Das, Dr. Neelanarayan, “ IOT Based Anti Theft Flooring System” in IJESC , vol 10, no.4, pp. 25463-25466,2020. 4 Siddalingesha G.R, H. M. Shamita, “IOT Based Anti Theft System for home” in IRJET, vol 8, no. 10, pp. 509 – 513, 2021. 5 Sanjana Kute, Ruthvik Pimpalkar, Shivajirao S, “Theft Detection System” in IRE Journals, vol 4, no 10, 2456 – 2462, 2021. 6 Gaurav Sable, Gaurav Sharma, Manish Bhalerao, Yash Ramugade, “IOT Based Theft Detection using Raspberry Pi” in IJIRT, vol 11, no 12, 2356 – 2360, 2022. 7 Mohd Musab, Ms. Seema Kaloria, Ankit Chhipa, Anand Sharma, Fardeen Mansoori, “IOT Based Anti-Theft Security System” in IJRTI, vol 7, no 6, pp. 106 – 109, 2022. 8 Santosh Mahale, Shivam Gujrathi, Pratik Bramhecha, Kalyani Bedarkar, Rohini Shinde, Yashraj Patil, “Anti-Theft Detection System” in IJIRSET, vol 9, no 4, pp. 1889 – 1895, 2020. 9 Sharnil Pandya, Hemant Ghayvat, Ketan Kotecha, Mohammed Awais, Saeed Akbarzadeh, Prosanta Gope , Subhas Chandra Mukhopadhyay and Wei Chen, “Smart Home Anti-Theft System” in applied system innovation, vol 1, no 42, pp. 1-22, 2018 https://doi.org/10.3390/asi1040042 10 Mr. Vikrant A. Agaskar, “ IOT BASED IOT Based Theft Detection” in IJCRT, vol 6, no 2, pp. 231 – 234, 2018..
Bhavya, Nalini, Deepika, Nagaraj, and Jagadamba. International Journal of Innovative Research in Information Security, 9 (2):
10-14(May 2023)1. Adler, A.; Schuckers, S. Biometric vulnerabilities, overview. In Encyclopedia of Biometrics; Li, S.Z., Jain, A., Eds.; Springer: Boston, MA, USA, 2009. https://doi.org/10.1007/978-0-387-73003-5_65 2. Nguyen, H.T. Fingerprints Classification through Image Analysis and Machine Learning Method. Algorithms 2019, 12, 241. https://doi.org/10.3390/a12110241 3. Biometric Systems Lab—FVC2000: Fingerprint Verification Competition. Available online: FVC2000 (unibo.it)(accessed on 22 January 2021). 4. Tang, Y.; Gao, F.; Feng, J. Latent fingerprint minutia extraction using fully convolutional network. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics, Denver, CO, USA, 1–4 October 2017; pp. 117–123. https://doi.org/10.1109/btas.2017.8272689 5. Huang, X.; Qian, P.; Liu, M. Latent fingerprint image enhancement based on progressive generative adversarial network. In Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA, 14–19 June 2020; pp. 3481–3489. https://doi.org/10.1109/cvprw50498.2020.00408 6. Neurotechnology Company—Sample Fingerprint Databases. Available online: Download biometric algorithm demo software, SDK trials, product brochures. (neurotechnology.com)(accessed on 22 January 2021). 7. Fingerprint Image identification for crime detection (2019) Fingerprint Image Identification for Crime Detection | IEEE Conference Publication | IEEE Xplore https://doi.org/10.1109/iccsp.2019.8698014.
B. Han. IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue VIII):
76-80(August 2020)1. Seenivasagam V, Velumani R, “A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud,” Computational and mathematical methods in medicine, 2013. 2. Parah S A , Sheikh J A , Ahad F , et al, “Information hiding in medical images: a robust medical image watermarking system for E-healthcare, “Multimedia Tools & Applications, vol. 76,no.8, pp.1-35.,2017 3. Aparna, Puvvadi , and P. V. V. Kishore , “Biometric-based efficient medical image watermarking in E-healthcare application,”IET Image Processing,vol .13,no.3 , pp.421-428,2019. 4. Aparna, Puvvadi , and P. V. V. Kishore , “An iris biometric-based dual encryption technique for medical image in e-healthcare application,” International Journal of Computational Vision and Robotics, vol.10,no.1,2020,:. 5. Raul R C, Claudia F U, Trinidad-Bias G J, “ Data Hiding Scheme for Medical Images,” Electronics, Communications and Computers, 2007. CONIELECOMP '07. 17th International Conference on. IEEE, pp.32-32,2007. 6. Singh A K, Kumar B, Dave M, et al , “Robust and imperceptible dual watermarking for telemedicine applications,” Wireless Personal Communications, vol.80,no.4, pp.1415-1433,2015 7. Aparna, Puvvadi , and P. V. V. Kishore , “A blind medical image watermarking for secure e-healthcare application using crypto-watermarking system,” Journal of Intelligent Systems ,2019. 8. Singh A K, Kumar B, Dave M, et al, “ Multiple watermarking on medical images using selective discrete wavelet transform coefficients,” Journal of Medical Imaging & Health Informatics, vol 5,no.3, pp.607-614,2015. 9. Ghouti, Lahouari , “ Robust perceptual color image hashing using randomized hypercomplex matrix factorizations,” Multimedia Tools and Applications ,vol77,no15,pp:19895-19929,2018 10. Cui, Yan , et al, “Supervised discrete discriminant hashing for image retrieval,” Pattern Recognition ,vol78,pp:79-90,2018.
Utkarsh, Sudhanshu, Devansh, Parth, and Ajay. International Journal of Innovative Research in Information Security, Volume VII (Issue IV):
42(46 2020)1. Dudgeon, D.E. and R.M. Mersereau, Multidimensional Digital Signal Processing. 1984, Englewood Cliffs, New Jersey: Prentice-Hall. 2. Castleman, K.R., Digital Image Processing. Second ed. 1996, Englewood Cliffs, New Jersey: Prentice-Hall. 3. Oppenheim, A.V., A.S. Willsky, and I.T. Young, Systems and Signals. 1983, Englewood Cliffs, New Jersey: Prentice-Hall. 4. Papoulis, A., Systems and Transforms with Applications in Optics. 1968, New York: McGraw-Hill. Russ, J.C., The Image Processing Handbook. Seconded. 1995, Boca Raton, Florida: CRC Press. 5. Giardina, C.R. and E.R. Dougherty, Morphological Methods in Image and Signal Processing. 1988, Englewood Cliffs, New Jersey: Prentice- Hall . 321. 6. Gonzalez, R.C. and R.E. Woods, Digital Image Processing. 1992, Reading, Massachusetts: Addison-Wesley. 716. 7. Goodman, J.W., Introduction to Fourier Optics. McGraw-Hill Physical and Quantum Electronics Series. 1968, New York: McGraw-Hill. 287..
Caroline, Micah, and Moses. IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue V):
108-116(July 2019)1. UNAIDS. (2018). The Global HIV/AIDS Epidemic. Retrieved August 2018, from hiv.gov: https://www.hiv.gov/hiv-basics/overview/data-and-trends/global-statistics 2. Kimberly, G. (2015). HIV service delivery models towards `zero AIDS related deaths. BMC Health service research.15(2) 12-15 3. Johnson, K. (2013). integration of HIV and family planning Health services in Sub-saharan Africa, DHS Analytical studies no. 30 Calverton, Maryland, USA. 4. Mutemwa, R. (2016). Perception and Experiences of Integrated Service Delivery Among Women Living with HIV Attending Reproductive Health Services in Kenya: A Mixed Methods Study. AIDS and behaviour, 20(9), 2130-40. 5. Bergh, A. (2015). Clinician Perceptions and Patient Experiences of ART Teatment and primary health care integration in ART clinics. AOSIS open journa, 38(1),1489l. 6. Sima, Belachew, & Abebe. (2017). Knowledge, Attitude and Perceived Stigma towards Tuberculosis among Pastoralists. Plos one, 12(7), 18-32 7. Pathmanathan, Munyaradzi, Sherri, Dokubo, Preko, Mazibuko, et al. (2017). High Uptake of Antiretroviral Therapy among HIV-positive TB Patients Receiving co-located Services in Swaziland. plos one, 13(5). 196-831 8. Buh, W., Peter, N., & Atashili, J. (2016). Clients satisfaction with HIV treatment services in Bamenda, Cameroon. BMchC Health services Resear, 16(1), 280. 9. Kikuvi, J. (2014). Are integrated HIV services less stigmatizing than stand alone models of care? A comparative case study from Swaziland. International Aids Society. 10. Kioko, J. (2015). Are integrated HIV services less stigmatizing than stand alone models of care? A comparative case study from Swaziland. Journal Of International Aids Society, 16(1), 9-12. 11. National AIDS Control Council,NACC. (2016). Kenya HIV County Profiles. Nairobi: Ministry Of Health 12. Odeny. T, K. J. (2013). Intergration of HIV Core with Primary Health Care services:Effects of patient satisfaction and stigma in Rural Kenya. AIDS Resersch and Treatment, 20(2), 4-8..
Basha, Abdulreda, and Hatem. IRJCS:: International Research Journal of Computer Science, Volume VI (Issue III):
38-46(March 2019)1. R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility," Future Generation computer systems, vol. 25, pp. 599-616, 2009. 2. P. Mell and T. Grance, "The NIST definition of cloud computing," 2011. 3. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, et al., Ä view of cloud computing," Communications of the ACM, vol. 53, pp. 50-58, 2010. 4. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, et al., Äbove the clouds: A berkeley view of cloud computing," Technical Report UCB/EECS-2009-28, EECS Department, University of California, Berkeley2009. 5. I. Foster, Y. Zhao, I. Raicu, and S. Lu, "Cloud computing and grid computing 360-degree compared," in Grid Computing Environments Workshop, 2008. GCE'08, 2008, pp. 1-10. 6. B. Hayes, "Cloud computing," Communications of the ACM, vol. 51, pp. 9-11, 2008. 7. D. Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman, L. Youseff, et al., "The eucalyptus open-source cloud-computing system," in Cluster Computing and the Grid, 2009. CCGRID'09. 9th IEEE/ACM International Symposium on, 2009, pp. 124-131. 8. R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, and R. Buyya, "CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms," Software: Practice and experience, vol. 41, pp. 23-50, 2011. 9. L. M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner, Ä break in the clouds: towards a cloud definition," ACM SIGCOMM Computer Communication Review, vol. 39, pp. 50-55, 2008. 10. S. Marston, Z. Li, S. Bandyopadhyay, J. Zhang, and A. Ghalsasi, "Cloud computing—The business perspective," Decision support systems, vol. 51, pp. 176-189, 2011. 11. A. D. Basha, I. N. Umar, and M. Abbas, "Mobile applications as cloud computing: implementation and challenge," International Journal of Information and Electronics Engineering, vol. 4, p. 36, 2014. 12. C. Shravanthi and H. Guruprasad, "Mobile cloud computing as future for mobile applications," International Journal of Research in Engineering and Technology, vol. 3, pp. 2319-2322, 2014. 13. N. Patil, N. Patil, A. Bagal, M. Desai, and A. Bhosale, "Development of Android Mobile Application for Cloud Video Streaming using Mobile Cloud Computing." 14. A. D. Basha, "Modeling E-Learning Readiness among Instructors in Iraqi Public Universities," Universiti Sains Malaysia, 2015. 15. K. Patil and S. Patil, Ä CASE STUDY ON MOBILE CLOUD COMPUTING." 16. M. A. Mahmod, A. B. M. Ali, A. R. B. Ahlan, A. Shah, and M. S. A. Seman, "E-learning in Iraqi universities: A review," in Computing, Engineering, and Design (ICCED), 2017 International Conference on, 2017, pp. 1-4. 17. A. D. Basha, S. H. Mnaathr, I. N. Umar, and R. Jamaludin, "Insight on Protection of Universities Networks Information Security: The Problems and the Solutions," 2013. 18. E. M. Morgado and R. Schmidt, "Increasing Moodle resources through cloud computing," in Information Systems and Technologies (CISTI), 2012 7th Iberian Conference on, 2012, pp. 1-4. 19. M. Wang, Y. Chen, and M. J. Khan, "Mobile cloud learning for higher education: A case study of Moodle in the cloud," The International Review of Research in Open and Distributed Learning, vol. 15, 2014. 20. V. Siládi and V. Mižúrová, "LMS Moodle on Computing Cloud," in 4th Interantional Scientific Conference in V4 Countries, Applied Natural Sciences, Trnava, 2013. 21. V. Kumar and D. Sharma, "Creating Collaborative and Convenient Learning Environment Using Cloud-Based Moodle LMS: An Instructor and Administrator Perspective," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), vol. 11, pp. 35-50, 2016. 22. N. Sclater, "eLearning in the Cloud," International Journal of Virtual and Personal Learning Environments, vol. 1, pp. 10-19, 2012..
A. Abdulameer, H. M., S. Alrazak, and S. Lu. IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VIII):
475-485(October 2018)1. Chalom, Edmond, Eran Asa, and Elior Biton. "Measuring image similarity: an overview of some useful applications." IEEE Instrumentation & Measurement Magazine 16.1 (2013): 24-28. 2. Chandler, Damon M. "Seven challenges in image quality assessment: past, present, and future research." ISRN Signal Processing 2013 (2013). 3. Chandler, Damon M., Md Mushfiqul Alam, and Thien D. Phan. "Seven challenges for image quality research." Human Vision and Electronic Imaging XIX. Vol. 9014. International Society for Optics and Photonics, 2014. 4. Lajevardi, Seyed Mehdi, and Zahir M. Hussain. "Zernike moments for facial expression recognition." rn 2 (2009): 3. 5. Lajevardi, Seyed Mehdi, and Zahir M. Hussain. "Higher order orthogonal moments for invariant facial expression recognition." Digital Signal Processing 20.6 (2010): 1771-1779. 6. Pass, Greg, and Ramin Zabih. "Comparing images using joint histograms." Multimedia systems 7.3 (1999): 234-240. 7. Shnain, Noor Abdalrazak, Zahir M. Hussain, and Song Feng Lu. Ä feature-based structural measure: An image similarity measure for face recognition." Applied Sciences 7.8 (2017): 786. 8. Wang, Zhou, et al. "Image quality assessment: from error visibility to structural similarity." IEEE transactions on image processing 13.4 (2004): 600-612. 9. Zhang, Lin, et al. "FSIM: a feature similarity index for image quality assessment." IEEE transactions on Image Processing20.8 (2011): 2378-2386. 10. Aljanabi, Mohammed Abdulameer, Zahir M. Hussain, and Song Feng Lu. Än entropy-histogram approach for image similarity and face recognition." Mathematical Problems in Engineering 2018 (2018). 11. Aljanabi, Mohammed Abdulameer, Noor Abdalrazak Shnain, and Song Feng Lu. Än image similarity measure based on joint histogram—Entropy for face recognition." Computer and Communications (ICCC), 2017 3rd IEEE International Conference on. IEEE, 2017. 12. Hwang, Sun-Kyoo, and Whoi-Yul Kim. Ä novel approach to the fast computation of Zernike moments." Pattern Recognition 39.11 (2006): 2065-2076. 13. Canny, John. Ä computational approach to edge detection." IEEE Transactions on pattern analysis and machine intelligence 6 (1986): 679-698. 14. Picard, C. F. "The use of information theory in the study of the diversity of biological populations." Proc. Fifth Berk. Symp. IV. 1979. 15. Ponomarenko, Nikolay, et al. "TID2008-a database for evaluation of full-reference visual quality assessment metrics." Advances of Modern Radioelectronics 10.4 (2009): 30-45. 16. Ninassi, A., P. Le Callet, and F. Autrusseau. "Subjective quality assessment-IVC database." online http://www. irccyn. ec-nantes. fr/ivcdb (2006). 17. “Laboratories, A.T. The Database of Faces,” http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html 18. “FEI Face Database,” http://fei.edu.br/∼cet/facedatabase.html.
Pooja, and Ahirao. IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VIII):
471-474(September 2018)1. K. Wu and C. Wang, “Steganography using reversible texture synthesis” IEEE Transactions on Image Processing Vol.24 pp 130-139,January 2015 2. Shreyank N Gowda, “An Advanced Diffie-Hellman Approach to Image Steganography ” IEEE Transactions on advance network and telecommunication system Vol.19 pp 1-4,june 2016 3. Sherin Sugathan, “An Improved LSB Embedding Technique for Image Steganography ” International conference on applied and theoretical computing and communication technology Vol.33 pp 609-612,2016 4. S. Singh and V. K. Attri Dual Layer Security of data using LSB Image Steganography Method and AES Encryption Algorithm International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 8, No. 5 , pp. 259-266 ,2015 5. Utsav Sheth and Shiva Saxena, “Image Steganography Using AES Encryption and Least Significant Nibble ” International conference on communication and signal processing Vol.11 pp 0876-0879,2016 6. Radu Pietraru, “Secure communication method based on encryption and steganography” International conference on control system and computer science Vol.31 pp 453-458,2017 7. Y Manjula and K B Shivakumar ,”Enhanced Secured Image Steganography using Double Encryption Algorithm” International Conference on Computing for Sustainable Global Development (IndiaCom),2016 8. Tanushree Shelare and Varsha Powar,”A secure transmission approach using B-Trees in steganography”International Conference on Automatic Control and Dynamic Optimization Techniques,2016 9. https://www.sans.org/reading-room/whitepapers/vpns/review-chaffing-winnowing-876 10. http://www.asp.net/: This is the official Microsoft ASP.NET web site. It has a lot of: tutorials, training videos, and sample projects. 11. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6850714&queryText%3Dimage+steganography 12. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6658020&queryText%3Dimage+steganography.