Naslov
Classification of Test Documents Based on Handwritten Student ID's Characteristics

Autori
Čelar, Stipe ; Stojkić, Željko ; Šeremet, Željko ; Marušić, Željko ; Zelenika, Danijel

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Procedia Engineering, Volume 100-2015 / Katalinic, B. - Beč : Elsevier, 2015, 782-790

Skup
25th International DAAAM Symposium

Mjesto i datum
Beč, Austrija, 26.11.2014. - 29.11.2014

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Bag of Words ; Image categorization ; Neural Network ; Recognition of Handwritten Digits ; Visual vocabularie

Sažetak
The bag of words (BoW) model is an efficient image representation technique for image categorization and annotation tasks. Building good feature vocabularies from automatically extracted image feature vectors produces discriminative feature words, which can improve the accuracy of image categorization tasks. In this paper we use feature vocabularies based biometric characteristic for identification on student ID and classification of students' papers and various exam documents used at the University of Mostar. We demonstrated an experiment in which we used OpenCV as an image processing tool and tool for feature extraction. As regards to classification method, we used Neural Network for Recognition of Handwritten Digits (student ID). We tested out proposed method on MNIST test database and achieved recognition rate of 94, 76% accuracy. The model is tested on digits which are extracted from the handwritten student exams and the accuracy of 82% is achieved (92% correctly classified digits).

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA