Attendance System Essay Example
Attendance System Essay Example

Attendance System Essay Example

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  • Pages: 4 (1591 words)
  • Published: August 26, 2018
  • Type: Essay
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Every organization whether it be an educational institution or business organization, it has to maintain a proper record of attendance of students or employees for the functioning of organization. Designing a better attendance management system for students so that records be maintained with ease and accuracy was an important key behind motivating this project.

Thanks to the similarity to the way of human ngerprint experts and compactness of templates, the minutiae-based matching method is the most widely studied matching method. Fingerprints are considered to be the best and fastest method for biometric identification. They are secure to use, unique for every person and does not change in one’s lifetime. Besides these, implementation of ngerprint recognition system is cheap, easy and accurate up to satis ability. Fingerprint recognition has been widely used in both forensic and civilian applications.

Compared with other biometrics features, ngerprint-based biometrics is the most proven technique and has the largest market share. Not only it is faster than other techniques but also the energy consumption by such systems is too less. Using a ngerprint recognition system for attendance management Managing attendance records of students of an institute is a tedious task. It consumes time and paper both. To make all the attendance related work automatic and on-line, we have designed an attendance management system which could be implemented in NIT Rourkela.

It uses a cation system developed in this project. This ngerprint identification system uses existing as well as new techniques in ngerprint recognition and matching. A new one to many matching algorith


m for large databases has been introduced in this identification system. Attendance Management Framework Manual attendance taking and report generation has its limitations.

It is well enough for 30-60 students but when it comes to taking attendance of students large in number, it is difficult. For taking attendance for a lecture, a conference, etc. oll calling and manual attendance system is a failure. Time waste over responses of students, waste of paper etc. are the disadvantages of manual attendance system. Moreover, the attendance report is also not generated on time.

Attendance report which is circulated over NITR webmail is two months old. To overcome these non-optimal situations, it is necessary that we should use an automatic on-line attendance management system. So we present an implementable attendance management framework. Student attendance system framework is divided into three parts: Hardware/Software Design, Attendance Management Approach and On-line Report Generation.

LCD display will be displaying rolls of those whose attendance is marked. Computer Software will be interfacing with the ngerprint scanner and LCD and will be connected to the network. It will input ngerprint, will process it and extract features for matching. After matching, it will update database attendance records of the students.

Computer software will start the process after inputting the ngerprint of teacher. It will nd the Subject ID, and Current Semester using the ID of the teacher or could be set manually on the software. If teacher doesn’t enter classroom, attendance marking will not start. After some time, say 20 minutes of this process, no attendance will

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be given because of late entrance.

We cannot use wireless LAN here because fetching data using wireless LAN will not be possible because of less range of wireless devices. So enrolled data would be on chip itself. Attendance results will be updated when portable device will be in the range of nodes which are storing attendance reports. We may update all the records online via the mobile network provided by different companies.

Today 3G network provides s client throughput which can be used for updating attendance records automatically without going near nodes. It will be fetched by using 3G mobile network from central database repository. The design of such a portable device is the task of embedded system engineers. The device may either be having touchscreen input/display or buttons with lcd display. A software specially designed for the device will be running on it. Teachers will verify his/her ngerprint on the device before giving it to students for marking attendance.

After verifying the teacher’s identity, software will ask for course and and other required information about the class which he or she is going to teach. Software will ask teacher the time after which device will not mark any attendance. This time can vary depending on the teacher’s mood but our suggested value is 25 minutes. This is done to prevent late entrance of students. This step will hardly take few seconds. Then students will be given device for their ngerprint identification and attendance marking. In the continuation, teacher will start his/her lecture.

Students will hand over the device to other students whose attendance is not marked. After 25 minutes or the time decided by teacher, device will not input any attendance. After the class is over, teacher will take device and will end the lecture. The main function of software running on the device will be the ngerprint identification of students followed by report generation and sending reports to servers using 3G network. Other functions will be downloading and updating the database available on the device from central database repository.

There are various other kind of student attendance management systems available like RFID based student attendance system and GSM-GPRS based student attendance system. These systems have their own pros and cons. Our system is better because rst it saves time that could be used for teaching. Second is portability. While GSM-GPRS based systems use position of class for attendance marking which is not dynamic and if schedule or location of the class changes, wrong attendance might be marked.

Problem with RFID based systems is that students have to carry RFID cards and also the RFID detectors are needed to be installed. Nonetheless, students may give proxies easily using friend’s RFID card. These problems are not in our system. We used ngerprints as recognition criteria so proxies cannot be given. If portable devices are used, attendance marking will be done at any place and any time. So our student attendance system is far better to be implemented at NITR.

So we remove noises and enhance their quality. We extract features like minutiae and

others for matching. If the sets of minutiae are matched with those in the database, we call it an identi edngerprint. After matching, we perform post-matching steps which may include showing details of identified candidates, marking attendance etc.

The extraction of noisy and false minutiae can be done by applying minutiae extraction algorithm to the background regions of the image. Thus, segmentation is a process by which we can discard these background regions, which results in more reliable extraction of minutiae points. We are going to use a method based on variance thresholding . The background regions exhibit a very low grey - scale variance value , whereas the foreground regions have a very high variance . Firstly , the image is divided into blocks and the grey-scale variance is calculated for each block in the image .

One very useful property of the Gabor filter is that it contains a DC component of zero, which indicates that the resulting ltered image has a zero mean pixel value. Hence, binarisation of the image can be done by using a global threshold of zero. Binarisation involves examining the grey-level value of every pixel in the enhanced image, and, if the grey-level value is greater than the prede ned global threshold, then the pixel value is set to value one; else, it is set to zero.

The outcome of binarisation is a binary image which contains two levels of information, the background valleys and the foreground ridges. Thinning is a morphological operation which is used to remove selected foreground pixels from the binary images. A standard thinning algorithm is used, which performs this operation using two subiterations.

The algorithm can be accessed by a software MATLAB via the ‘thin’ operation of the bwmorph function. Each subiteration starts by examining the neighborhood of every pixel in the binary image, and on the basis of a particular set of pixel-deletion criteria, it decides whether the pixel can be removed or not. These subiterations goes on until no more pixels can be removed.

Advantage of using key is that, we do not perform full matching every time for non-matching minutiae sets, as it would be time consuming. For large databases, if we go on matching the full minutiae set for every enrolled ngerprint, it would waste time unnecessarily. Two types of keys are proposed - simple and complex. Simple key has been used in this project.

Due to inaccuracy and imperfection of reference point detection algorithm, we used centroid of all minutiae for construction of key. Complex Key The complex key stores more information and is structurally more complex. It stores vector of minutiae in which next minutiae is closest to previous minutiae, starting with reference point or centroid of all minutiae.

Key matching and full matching are performed using the matching algorithm discussed in later section. The matching algorithm will be involving matching the key of the query ngerprint with the many keys of the database. Those which matches ,their full matching will be processed, else the query key will be matched with next M keys and

so on.

In this method, we match ith minutiae of query set with k unmatched minutiae of sample set. Both the query sets and sample sets must be in sorted order of distance from reference point or centroid. ith minutia of query minutiae list is matched with top k unmatched minutiae of database minutiae set.