Pregled bibliografske jedinice broj: 703949
Automatic recognition of handwritten corrections for multiple-choice exam answer sheets
Automatic recognition of handwritten corrections for multiple-choice exam answer sheets // Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronic MIPRO 2014, Intelligent Systems (CIS) / Biljanović, Petar (ur.).
Rijeka, 2014. str. 1386-1391 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 703949 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Automatic recognition of handwritten corrections for multiple-choice exam answer sheets
Autori
Čupić, Marko ; Brkić, Karla ; Hrkać, Tomislav ; Mihajlović, Željka ; Kalafatić, Zoran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronic MIPRO 2014, Intelligent Systems (CIS)
/ Biljanović, Petar - Rijeka, 2014, 1386-1391
Skup
37th International Convention on Information and Communication Technology, Electronics and Microelectronic MIPRO 2014, Intelligent Systems (CIS)
Mjesto i datum
Opatija, Hrvatska, 26.05.2014. - 30.05.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
character recognition ; handwritten letters ; Weka ; random forest classifier
Sažetak
Automated grading of multiple-choice exams is of great interest in university courses with a large number of students. We consider an existing system in which exams are automatically graded using simple answer sheets that are annotated by the student. A sheet consists of a series of circles representing possible answers. As annotation errors are possible, a student is permitted to alter the annotated answer by annotating the“error” circle and handwriting the letter of the correct answer next to the appropriate row. During the scanning process, if an annotated“error” circle is detected, the system raises an alarm and requires intervention from a human operator to determine which answer to consider valid. We propose rather simple and effecive computer vision algorithm which enables automated reading of a limited set of handwritten answers and minimizes the need for a human intervention in the scanning process. We test our algorithm on a large dataset of real scanned answer sheets, and report encouraging performance rates.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Tomislav Hrkać
(autor)
Karla Brkić
(autor)
Zoran Kalafatić
(autor)
Marko Čupić
(autor)
Željka Mihajlović
(autor)