Automated Monitoring Attendance System Essay

1.1 The problem and its mountain chainIn this paper we propose a system that automates the whole process of taking attention and maintaining its write naps in an academic institute. Managing people is a difficult trade union movement for most of the organizations, and maintaining the att remainder record is an important factor in people management. When considering academic institutes, taking the attention of students on daily basis and maintain the records is a major task. manual(a)ly taking the attendance and maintaining it for a long eon adds to the difficulty of this task as well as waste a lot of time.For this condition an efficient system is designed. This system takes attendance electronic in ally with the help of a thumbprint sensing element and all the records argon saved on a computer server. leafprint sensors and liquid crystal display screens atomic number 18 placed at the grip of each room. In order to mark the attendance, student has to place his/her flip out on the fingerprint sensor. On acknowledgement students attendance record is modifyd in the database and he/she is notified with LCD screen. No brace of all the stationary material and special soulal for keeping the records. more thanover an automated system replaces the manual system.1.2 IntroductionNowadays, industry is experiencing many technological advancement and changes in modes of learning. With the rise of globalization, it is becoming essential to stimulate an easier and more effective system to help an organization or company. In bitchiness of this matter, thither argon still business establishments and schools that workout of goods and services the old-fashioned way. In a certain way, one thing that is still in manual process is the recording of attendance. After having these issues in mind we develop an change Monitoring Attendance arranging, which automates the whole process of taking attendance and maintaining it, plus it holds an accurate records .Biometric systems have been widely utilize for the purpose of realization. These realisation methods touch on to automatic recognition of people found on the some special physiological or behavioral features 1. at that place are many biometrics that can be utilized for some specific systems but the signalise structure of a biometric system is always same 2. Biometric systems are staple fibreally use for one of the twain objectives identification 3 or verification 4. denomination means to find a match mingled with the query biometric adjudicate and the one that is already been stored in database 5. For example to pass through a restricted area you may have to scan your finger through a biometric device. A new template testament be generated that impart be then compared with the previously stored templates in database. If match found, then the mortal leave alone be allowed to pass through that area.On the other move over verification means the process of checking whether a query biometric sample belongs to the claimed individualism or not 6. most of the most honey oilly utilize biometric systems are (i) Iris recognition, (ii) Facial recognition,(iii) fingerprint identification, (iv) Voice identification, (v) DNA identification, (vi) Hand geometry recognition and (viii)Signature cheque 5.Previously the biometrics techniques were used in many areas such as edifice security, ATM, credit cards, criminal investigations and passport control 4. The proposed system uses fingerprint recognition technique 1 for obtaining students attendance. Human beings have been using fingerprints for recognition purposes for a very(prenominal) long time 7, because of the simplicity and accuracy of fingerprints.Finger print identification is based on twain factors (i) Persistence the basic characteristics and features do not change with the time. (ii) Individuality fingerprint of each person in this foundation is unique 8. Modern fingerprint twin(a) tec hniques were initiated in the late 16th century 9 and have added most in twentieth century. Fingerprints are considered one of the most mature biometric technologies and have been widely used in forensic laboratories and identification units 10. Our proposed system uses fingerprint verification technique to automate the attendance system. It has been proved over the years that fingerprints of each every person are unique 8. So it helps to uniquely identify the students.1.3 hypothetic BackgroundFor over 100 years, fingerprint has been used to identify people. As one of the biometric identification, fingerprint is the quite the most popular one. Besides acquire the print for fingerprint is easy, it doesnt need a special sophisticated hardware and software product to do the identification. In the old times and blush until now, fingerprints are usually taken using merely inks and papers (could be one print, ten prints, or latent print). Finger print is unique. on that point is no c ase where two fingerprints are found to be scarce identical.During the fingerprint matching process, the covers of the two fingerprints result be compared. Besides using ridges, some of the identification techniques also use minutiae. In brief, minutiae can be described as point of interest in fingerprints. Many types of minutiae have been defined, such as pore, delta, island, ridge ending, bifurcation, spurs, bridges, crossover, etc, but commonly only two minutiae are used for their stability and robustness (4), which are ridge ending and bifurcation.To help in fingerprint identification, fingerprint classification method is implemented. There are some classification theories applicable in the real world such as The NCIC System (National Crime knowledge Center) Still used even out until now, the NCIC system classifies fingers according to the combination of patterns, ridge counts, whorl tracing. NCIC determines.Fingerprint potpourri (FPC) field codes to represent the finger print characteristics. The following are the field codes tables using NCIC system FPC Field Codes eliminates the need of the fingerprint image and, thus, is very face-saving for the need of fingerprint identification for those who do not have get to to an AFIS. Instead of relying to the image, NCIC relies more on the finger image information. The atomic number 1 and American sorting Systems Henry and American classification systems, although has a lot in common, are actually two different systems developed by two different people. The Henry Classification System (5) was developed by Sir Edward Henry in 1800s used to record criminals fingerprints during Civil War. Henry System used all ten fingerprints with the right thumb denoted number 1, right petite left finger denoted number 5, left thumb denoted number 6, and in conclusion the left little finger denoted number 10.According to Henry System, there were two classifications the main(a) and the secondary. In the primary class ification, it was a whorl that gives the finger a jimmy. While even numbered fingers were hard-boiled as the nominator, odd numbered fingers were treated as denominator. Each fingers value was equal to the value of the whorl plus one. In the secondary classification, each hands index finger would be designate a special enceinte letter taken from the pattern types (radial enlace (R), tented loop (T), ulnar loop (U), and arch (A)). For other fingers except those two index fingers, they were all assigned with small letter which was also known as small letter group. Furthermore, a sub secondary classification existed it was the grouping of loops and whorls, which coded the ridge of the loops and ridge tracings of whorls in the index, middle, and ring fingers. The following is the table of Henry System.The American Classification System was developed by Captain James Parke. The digression lies in assigning the primary value, the paper used to file the fingerprint, and the primary v alues calculation.Filing SystemsIn this system, all of the fingerprints are stored in lockers. Each cabinet contains one different classification and, thus, the fingerprint cards are stored accordingly. The creative activity of AFIS system greatly helps the classification process. There is no need to even store the physical fingerprint cards. AFIS does not need to count the primary values of all those fingers and does not have to be as heterogeneous as NCIC System. With the power of image recognition and classification algorithm, fingerprint identification can be done automatically by comparing the generator digital image to the target database containing all saved digital images. other important issue to know is the fingerprint classification patterns. These patterns are ripening with each generation of AFIS and differ from one too to other, searching time and reduced computational complexity.The first known strike of fingerprint classification was proposed by in 1823 by Pu rkinje, which resulted in fingerprint classification down into 9 categories transverse curve, central longitudinal strain, oblique stripe, oblique loop, sweet almond whorl, spiral whorl, ellipse, circle, and double whorl. Later on, more in depth study was conducted by Francis Galton in 1892, resulted in fingerprint classification down into 3 major classes arch, loop, and whorl. Ten years subsequent, Edward Henry refined Galtons experiment, which was later used by many law enforcement agencies worldwide. Many variations of Henry Galtons classification schemes exists, however there are 5 most common patterns arch, tented arch, left loop, right loop, and whorl. The following are types of fingerprint classification patternsSince IDAFIS is another extended form of AFIS, we do not need to implement all other classification systems. What we need to do is to see what kind of classification pattern the algorithm can distinguish.Fingerprint MatchingIn general, fingerprint matching can be cat egorized down into three categories Correlation-based matching the matching process begins by superimposing (lying over) two fingerprints, and calculating the correlation between both by taking displacement (e.g. translation, rotation) into account. Minutiae based matching Minutiae are first extracted from each fingerprint, aligned, and then calculated for their match. Ridge feature based matching Ridge patterns are extracted from each fingerprint and compared one with another. The difference with minutiae based is that kind of of extracting minutiae (which is very difficult to do to low prize fingerprint image) ridge pattern such as local penchant and frequency, ridge shape, and texture information is used.Chapter TwoMost of the attendance systems use paper based methods for taking and calculating attendance and this manual method requires paper sheets and a lot of stationery material. Previously a very few work has been done relating to the academic attendance monitoring problem. Some softwares have been designed previously to keep rails of attendance 11.But they require manual entry of data by the ply workers. So the problem remains unsolved. Furthermore idea of attendance introduce systems using facial recognition techniques have also been proposed but it requires pricey apparatus still not getting the required accuracy 12. machine-controlled Monitoring Attendance System is divided into three parts ironware/Software Design, regains for scrape attendance and Online Attendance Report. Each of these is explained below. 2 System Description2 .1 HardwareRequired hardware used should be easy to maintain, implement and easily available. Proposed hardware consists following parts(1) Fingerprint Scanner(2) LCD Screen(3) ComputerFingerprint scanner will be used to input fingerprint of teachers/students into the computer software. LCD screening will be displaying rolls of those whose attendance is mark. Computer Software will be interfacing fingerpr int scanner and LCD and will be connected to the lucre. It will input fingerprint, will process it and extract features for matching. After matching, it will update the database attendance records of the students. A fingerprint sensor device along with an LCD screen is placed at the entrance of each classroom. The fingerprint sensor is used to capture the fingerprints of students while LCD screen notifies the student that his/her attendance has been marked.2 .2 Rules for marking attendanceThis part explains how students and teacher will use this attendance management system. avocation points will make sure that attendance is marked correctly, without any problem (1) All the hardware will be outside of the classroom.(2) When teacher enters the classroom, the attendance marking will start. Computer software will start the process after inputting fingerprint of the teacher. It will find the Subject ID and current semester using the ID of the teacher or could be dictated manually on the software. If the teacher doesnt enter the classroom, attendance marking will not start. (3) After some time, say 15 proceeding of this process. The student who login after this time span will be marked as late on the attendance. This time period can be increased or decreased per requirements.2 .3 Online Attendance ReportDatabase for attendance would be a table having following fields as a combination for primary field (1) Day, (2) Roll, (3) Subject and following non-primary fields (1) Attendance, (2) Semester. utilize this table, all the attendance can be managed for a student. For online report, a honest website will be made for it. Which will access this table for present attendance of students .The sq queries will be used for report generation? Following query will give total numbers of classes held in a certain subject. Now the attendance percent can easily be calculated2.4 Using wireless network instead of LANWe are using LAN for communication among servers and hard ware s in the classroom. We can instead use wireless LAN with portable devices. Portable device will have an embedded fingerprint scanner, wireless connection, amicroprocessor loaded with software, keeping and a display terminal.Source/References1 D. Maltoni, D. Maio, A. K. Jain, S. Prabhaker, Handbook of Fingerprint Recognition, Springer, invigorated York, 2003.2 A.C. Weaver, Biometric authentication, Computer, 39(2), pp 96 97 (2006). 3 J. Ortega Garcia, J. Bigun, D. Reynolds and J.Gonzalez Rodriguez, Authentication gets personal with biometrics, head Processing Magazine, IEEE, 21(2), pp 50 62 (2004).4 Anil K. Jain, Arun Ross and Salil Prabhakar, An introduction to biometric recognition , Circuits and Systems for image Technology, IEEE Transactions on Volume 14, Issue 1, Jan. 2004 Page(s)4 20. 5 Fakhreddine Karray, Jamil Abou Saleh, Mo Nours Arab and Milad Alemzadeh, Multi modal(prenominal) Biometric Systems A State of the Art Survey , Pattern Analysis and railroad car Intel ligence Laboratory, University of Waterloo, Waterloo, Canada. 6 Abdulmotaleb El Saddik, Mauricio Orozco, Yednek Asfaw, Shervin Shirmohammadi and Andy Adler A Novel Biometric System for Identification and hindrance of Haptic Users , Multimedia Communications search Laboratory (MCRLab) naturalise of Information Technology and Engineering University of Ottawa, Ottawa, Canada .7 H. C. Lee and R. E. Gaensslen, Advances in Fingerprint Technology , Elsevier, natural York . 8 Sharath Pankanti, Salil Prabhakar, Anil K. Jain, On the Individuality of Fingerprints , IEEE transaction on pattern compendium and machine intelligence, vol.24, no.8, August 2002. 9 Federal Bureau of Investigation, The Science of Fingerprints Classification and Uses , U. S. regimen Printing Office, Washington, D. C., 1984. 10 H. C. Lee and R. E. Gaensslen (eds.), Advances in Fingerprint Technology , Second Edition, CRC Press, immature York, 2001. 11 K.G.M.S.K. Jayawardana, T.N. Kadurugamuwa, R .G. Rage and S. Radhakrishnan , Timesheet An Attendance Tracking System , Proceedings of the Peradeniya University Research Sessions, Sri Lanka, Vol.13, Part II, 18th December 2008 .12 Yohei KAWAGUCHI, Tetsuo SHOJI , Weijane LIN ,Koh KAKUSHO , Michihiko MINOH , Face Recognition based sing Attendance System , Department of Intelligence Science and Technology, Graduate School of Informatics, KyotoUniversity. Academic Center for Computing and Media Studies, Kyoto University. 13 Digital Persona, Inc. t720 Bay road redwood City, CA 94063 USA 5, http//www.digitalpersona.comTable of ContentsChapter One1.1 The problem and its scope1.2 Introduction1.3 Theoretical BackgroundChapter Two2.1 Hardware and Software2.2 Rule for marking attendance2.3 Online Attendance Report2.4 Using Wireless network instead of LANChapter Three.Chapter Four4.1 Summary4.2 Conclusion and passport4.3 BibliographySource/References