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i-manager's Journal on Pattern Recognition (JPR)

Current Issue Vol. 11 Issue 2

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Volume 6 Issue 3 September - November 2019

Research Paper

A Speech Recognition Voice Control System for Visitor Directive in Osun State Polytechnic, Iree, Nigeria

Ogunwuyi Ogumakinde* , Olawuni Adeolu**

*-** Department of Electrical and Electronic Engineering, Osun State Polytechnic, Iree, Osun, Nigeria.

Ogumakinde, O., and Adeolu, O. (2019). A Speech Recognition Voice Control System for Visitor Directive in Osun State Polytechnic, Iree, Nigeria. i-manager’s Journal on Pattern Recognition, 6(3), 1-6. https://doi.org/10.26634/jpr.6.3.17231

Abstract

The purpose of this research is to demonstrate how a Voice Command System is implemented. The primary input of a user's voice is used in this method. We were able to convert voice as an input to text with speech to a text engine. The resulting text is used to process questions and collect relevant information. After collecting the information, it was converted to speech using speech-to-text and the correct output was delivered to the user. This research has realized a public API based speech recognition system with Raspberry Pi and USB microphone as hardware and several python programming languages. Osun State Polytechnic Iree has many different offices and lecture halls and the directory is done by signposts and asking people around the campus and there has been a great problem as some signposts have fallen off. While the signposts can only give a directive to buildings, it can't give the directive to offices inside the building and some visitors get embarrassed by the way they are replied to, some may be given the wrong direction while some may not get being replied at all. These prompts to design a system that gives visitors direction to offices and lecture rooms in Engineering building. The research covers the hardware specification of the speech recognition system and also maps an application of public speech APIs and shows a realization using appropriate hardware.

References

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[6]. Lee, I. J. (2011, September). An accident detection system on highway using vehicle tracking trace. In ICTC 2011 (pp. 716-721). IEEE

[7]. Nan, E., Radosavac, U., Papp, I., &Antić, M. (2017, September). Architecture of voice control module for smart home automation cloud. In 2017 IEEE 7th International Conference on Consumer Electronics- Berlin (ICCE-Berlin) (pp. 97-98). IEEE.

[8]. Olupohunda, B. (2012). The burden of illiteracy in Nigeria. The Punch Newspaper'Opinion, 37.

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Research Paper

Biometric Finger Prints Security System for Clock-In and Clock-Out for Primary School

Yahaya Mohammed Sani * , Marcel Peach Umeh, Mamman Adamu*

- Department of Information and Media Technology at the Federal University of Technology, Minna, Nigeria.

Department of Computer Science, Federal University of Technology, Minna, Nigeria.

Sani, Y. M., Umeh, M. P., and Adamu, M. (2019). Biometric Finger Prints Security System for Clock-In and Clock-Out for Primary School. i-manager’s Journal on Pattern Recognition, 6(3), 7-17. https://doi.org/10.26634/jpr.6.3.16906

Abstract

Security of life and property in any society is indispensable.Security is a major problem for both the government and the citizens of the global community, as it is obvious Nigeria is presently bedevilled with security challenges such as the kidnapping and abduction. This is because the high rate of abduction of primary and secondary pupils in the country is becoming alarming, the educational institution is gradually becoming a source of hostility and nightmare for a child. However, the proposed system was designed and implemented to effectively solve this problem with the use of fingerprint biometric technology, the system is designed to authenticate whoever is picking a child from school and authorise the student clock out for the day. The system reduces the risk of impersonation during student pick-up in school.

References

[1]. Akutu, G. (2017). The Guardian. Sunday Magazine, Retrieved from https://guardian.ng/sunday-magazi ne/creating-safe-environment-for-school-children /guardian.ng./

[2]. Almaqashi, S. (2019). GPS and CCTV based security monitoring system for the security of school GPS and CCTV based security monitoring system for the security of school children. International E- Research Journal.163, 82-88.

[3]. Anigbogu, S., David, M. S., & Anigbogu, G. (2015). Web based pre-school children monitoring system. International Journal of Trend in Research and Development, 2(6), 303–309.

[4]. Biometrics: authentication and identification (definition, trends, use cases, news) (2019). Retrieved from https://www.gemalto.com/govt/inspired /biometrics Causes-Effects-and-Solutions

[5]. Choudhary, A., Tripathi, A., Bajaj, A., Rathi, M. & Nandini, B. M. (2016). Automatic attendance system using face recognition, International Journal of Modern Trends in Engineering and Research (IJMTER), 3(4), 5-10.

[6]. Dwi, S., Joko, S., & Radityo, A. (2019). An android based course attendance system using face recognition, Journal of King Saud University-Computer and Information Sciences, 1-9. https://doi.org/10.1016/j.jksu ci.2019.01.0 06.

[7]. Elshaiekh, N., & Darai, S. (2017). Radio frequency identification school security system enhancement nour, Journal of Management Information Systems & ECommerce, 5(1), 7–13. https://doi.org/10.15640/jeds.v5 n1a2

[8]. Haidawati, N. A. K. K., Sairul, S. I., Sheroz, K., & Teddy, G. S. (2016). Fingerprint Biometric Systems. Retrieved from scialert.net: https://scialert.net/fulltext/?doi=t b.2016 .52.5 8

[9]. Hendry, R., Rahman, M. N. A., & Seyal, A. H. (2017). th Smart attendance system applying QR code. In 12 International Conference on Latest Trends in Engineering and Technology (ICLTET'2017) (pp. 22-24).

[10]. Iiechukwu, L. C., Uchem, C., & Asogwa, U. (2015). Stemming the incidence of kidnapping in the Nigerian society: What religious education can do. Journal of Culture, Society and Development, 12, 28-47.

[11]. Mohammed, K., Tolba, A. S & Elmogy, M. (2018). Multimodal student attendance management system( MSAMS), Ain Shams Engineering Journal, 9(4), 2917–2929. https://doi.org/10.1016/j.asej.201 8.08.002

[12]. Nazleen, S., & Rabu, A. (2018). The design and implementation of student attendance tracking system using QR code card. International Scientific Conference E-Learning and Software for Education, 3, 118-125. https://doi.org/10.12753/2066-026X-18-158

[13]. Ngwama, J. C. (2014). Kidnapping in Nigeria: An emerging social crime and the implications for the labour market. International Journal of Humanities and Social Science, 4(1), 133-145. https://tasdeeq.org/wpcontent/ uploads/2019/09/9.pdf

[14]. Okwuagbala, M. U. (2019). Kidnapping : Overview , Causes, Effects, and Solutions Kidnapping in Nigeria. Retrieved from https://owlcation.com/ socialsciences/ Kidnapping-Overview-

[15]. Physiological Modalities (2019). Retrieved from https://www.tutorialspoint.com/biometrics/physiologic al_ od alities.htm

[16]. Sarifah, P. R., Firdaus., & Dinda, I. (2018). An Integrated Child Safety using Geo-Fencing Information on Mobile Devices. Retrieved from ieeexplore: https://ieeexplore.ieee.org/docum ent/8605200

[18]. William, A., & Don, O. (2019). Nigeria's Kidnapping Crisis. Retrieved from https://enactafr ica.org/enactobserver/ nigerias-kidnapping-crisis

[19]. Yahya, F., Kushsairy , K., Haidawati, N., Sairul, S. I., Khan, S., & Gunawan, T. S. (2016). Fingerprint biometric systems. Trends in Bioinformatics, 9, 52-58. https://doi .org/10.3923/tb.2016.52.58

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Research Paper

Land Resource Management Through GIS and Remote Sensing

Jyoti Jain Tholiya*

Marathwada Mitramandal’s College of Architecture (MMCOA), Pune, Maharashtra, India.

Tholiya, J. J. (2019). Land Resource Management Through GIS and Remote Sensing. i-manager’s Journal on Pattern Recognition, 6(3), 18-26. https://doi.org/10.26634/jpr.6.3.16865

Abstract

Land use planning has been promoted as an important tool for sustainable use and management of land resources. Land use-Land cover classification is a fundamental dataset required in land use planning used by planners, legislatures, national, state and local planning agencies to overcome the problems such as uncontrolled development, haphazard growth, loss of agriculture land and deteriorating environmental quality. To make future action plans. This research paper focuses on conserving land resources to increase the welfare of the people through Geographic Information Systems (GIS) and Remote Sensing techniques. The current study proposes a Land Resource Action plan for arable land, wasteland, forest land and Hills. The alternative Land use systems have been recommended for different Land use-Land cover classes. The cropping pattern, improved agronomic practices, suitable crops, trees, and grasses have been suggested. For the development of forest, different soil-water conservation measures with afforestation of suitable species have been suggested as per land capability.

References

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[5]. Foody, G. M. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185-201. https://doi.org/10.1016/S0034-4257(01) 00295-4

[6]. Hossain, H., Sposito, V., & Evans, C. (2006). Sustainable land resource assessment in regional and urban systems. Applied GIS, 2(3), 24.1-24.21. https://doi. org/0.2104/ag060024

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[9]. Meyer, W. B., & Turner, B. L. (1992). Human population growth and global land-use/cover change. Annual Review of Ecology And Systematics, 23(1), 39-61.

[10]. Rindfuss, R. R., Walsh, S. J., Turner, B. L., Fox, J., & Mishra, V. (2004). Developing a science of land change: challenges and methodological issues. In Proceedings of the National Academy of Sciences,101(39), 13976- 13981. https://doi.org/10.1073/pnas.0401545101

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[13]. Yang, F., Zeng, G., Du, C., Tang, L., Zhou, J., & Li, Z. (2008). Spatial analyzing system for urban land-use management based on GIS and multi-criteria assessment modeling. Progress in Natural Science, 18(10), 1279- 1284. https://doi.org/10.1016/j.pnsc.2008. 05.007

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Research Paper

A Survey of Manuscripts Digitization to Restoration using Image Processing

Lalit Prakash Saxena*

Applied Research Section, Combo Consultancy, Obra, Sonebhadra, Uttar Pradesh, India.

Saxena, L. P. (2019). A Survey of Manuscripts Digitization to Restoration using Image Processing. i-manager’s Journal on Pattern Recognition, 6(3), 27-36. https://doi.org/10.26634/jpr.6.3.17302

Abstract

As of today, the physical condition of the manuscripts, most of them from ancient period, is deteriorating, creating issues in probable digitization and effective restoration procedures. A systematic approach in digitization and manuscripts restoration is going on, which involves image processing (mainly the acquisition) methods as a preventive measure. This paper presents a concise survey of classical and recent manuscript image processing methods. These documents have physical degradation, which prefers photographs rather than scanning, that may lead to further deterioration. This paper discusses the methodology, contributions, advantages, and disadvantages of the reviewed methods. Further, it also highlights the challenging problems in manuscripts image processing with the scope of future enhancements. The objective of this survey is to help researchers working in the domain of image processing, irrespective of the application areas.

References

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[5]. Brisinello, M., Grbić, R., Stefanovič, D., &Pečkai- Kovač, R. (2018, September). Optical character recognition on images with colorful background. In 2018, IEEE 8th International Conference on Consumer Electronics- Berlin (ICCE-Berlin), (pp. 1-6). IEEE. https://doi.org/10.1109/ICCE-Berlin.2018.8576202

[6] Calabretto, S., & Bozzi, A. (1998). The philological workstation bambi (better access to manuscripts and browsing of images). Journal of Digital Information, 1(3), 1- 17.

[7]. Chen, Y., & Leedham, G. (2005). Decompose algorithm for thresholding degraded historical document images. IEEE Proceedings-Vision, Image and Signal Processing, 152(6), 702-714. https://doi.org/10.10 49/ip-vis:20045054

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Review Paper

A Study of Anti Spoofing: Vital in Face Recognition Systems

Tanvi Joshi*

Department of Computer Science, Saffrony Institute of Technology, Gujarat, India.

Joshi, T. (2019). A Study of Anti Spoofing: Vital in Face Recognition Systems. i-manager’s Journal on Pattern Recognition, 6(3), 37-49. https://doi.org/10.26634/jpr.6.3.16927

Abstract

Face recognition is the second most widely used biometric approach after fingerprint. The applications of Face recognition are widely accepted and finding their space either at an organization or individual level due its adaptability among the people. But FR systems are vulnerable to spoofing attacks made by non-real human faces. Liveness detection is required for a secure program to protect against such spoofing. In this work, face liveness detection approaches are categorized based on types of techniques used for liveness detection. This classification helps in understanding various spoof attack scenarios and their relation to the formed solutions. A review of the previous works respect to face liveness detection is presented. The main objective is to outline the future development of a new and more secure liveness detection approach for face.

References

[1]. Albu, R. D. (2015, June). Face anti-spoofing based on Radon transform. In 2015, 13th International Conference on Engineering of Modern Electric Systems (EMES) (pp. 1-4). IEEE.

[2]. Ali, A., Deravi, F., & Hoque, S. (2012, September). Liveness detection using gaze collinearity. In 2012, Third International Conference on Emerging Security Technologies (pp. 62-65). IEEE. https://doi.org/10.1109/E ST.2012.12

[3]. Alotaibi, A., & Mahmood, A. (2016, June). Enhancing computer vision to detect face spoofing attack utilizing a single frame from a replay video attack using deep learning. In 2016, International Conference on Optoelectronics and Image Processing (ICOIP) (pp. 1-5). IEEE. https://doi.org/10.1109/OPTIP.20 16.7528488

[4]. Anjos, A., Chakka, M. M., & Marcel, S. (2013). Motion-based counter-measures to photo attacks in face recognition. IET biometrics, 3(3), 147-158. https://doi.org/1 0.1049/iet-bmt.2012.0071

[5]. Arashloo, S. R., Kittler, J., & Christmas, W. (2015). Face spoofing detection based on multiple descriptorfusion using multiscale dynamic binarized statistical image features. IEEE Transactions on Information Forensics and Security, 10 (11) , 2396 - 2407 . https://doi.org/10.1109/TIFS. 2015.2458700

[6]. Asaduzzaman, A., Mummidi, A., Mridha, M. F., & Sibai, F. N. (2015, December). Improving facial recognition accuracy by applying liveness monitoring technique. In 2015, International Conference on Advances in Electrical Engineering (ICAEE) (pp. 133-136). IEEE. https://doi.org/ 10.1109/ IC AEE.2015.7506814

[7]. Bao, W., Li, H., Li, N., & Jiang, W. (2009, April). A liveness detection method for face recognition based on optical flow field. In 2009, International Conference on Image Analysis and Signal Processing (pp. 233-236). IEEE. https://doi.org/10.1109/IASP.2009.5054589

[8]. Bharadwaj, S., Dhamecha, T. I., Vatsa, M., & Singh, R. (2013). Computationally efficient face spoofing detection with motion magnification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 105-110).

[9]. Bhardwaj, P., Debbarma, S., Deb, S., Debbarma, N., & Pal, J. (2012). Liveness detection using eye blink a case study. International Journal of Application or Innovation in Engineering & Management (IJAIEM), 1(3), 21-28.

[10]. Boulkenafet, Z., Komulainen, J., &Hadid, A. (2015, September). Face anti-spoofing based on color texture analysis. In 2015, IEEE International Conference on Image Processing (ICIP) (pp. 2636-2640). IEEE. https://doi.org /10.1109/ICIP.2015.7351280

[11]. Boulkenafet, Z., Komulainen, J., & Hadid, A. (2016). Face spoofing detection using colour texture analysis. IEEE Transactions on Information Forensics and Security, 11(8), 1818-1830. https://doi.org/10.1109/TIFS.2016.25 55286

[12]. Chingovska, I., Anjos, A., & Marcel, S. (2012, September). On the effectiveness of local binary patterns in face anti-spoofing. In 2012, BIOSIG-proceedings of the international Conference of Biometrics Special Interest Group (BIOSIG) (pp. 1-7). IEEE.

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