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Mobile based optical form evaluation system

Year 2016, Volume 22, Issue 2, 94 - 99, 01.05.2016

Abstract

Optical forms that contain multiple-choice answers are widely used both for electing students and evaluating student achievements in education systems in our country and worldwide. Optical forms are evaluated by employing optical mark recognition techniques through optical readers. High cost of these machines, limited access to them, long waiting time for evaluation results make the process hard for educationists working in cities or countries. In this study, a mobile application was developed for the educationists who own mobile phones or tablets for the purpose of evaluating students' answer sheets quickly and independent of location and optical readers. Optical form recognition, reading and evaluation processes are done on the image of student's answer sheet that is taken with the mobile phone or tablet of educationist. The Android based mobile application that we developed has a user-friendly interface, high success rate and is the first of our knowledge application that operates on mobile platforms in this field.

References

  • Monga H, Monga P, Kaur M. “A novel optical mark recognition technique based on biogeography based optimization”. International Journal of Information Technology and Knowledge Management, 5(2), 331-333, 2012.
  • Sen S, Bricka S. “Data collection technologies-past, present, and future”. 12th International Conference on Travel Behaviour Research, Jaipur, Rajasthan, India, 13-16 December 2009.
  • Syrex Corporation. “ICR, OCR and OMR - A Comparison of Technologies”. http://www.syrex.com.ph/Product/Download?filename =WhatIsOMR(26.04.2015).
  • Lucenteforte E, Collini F, Simonetti M, Messeri A, Caprilli S, Rasero L, Lapi F, Guidi G, Abeti MS, Mugelli A, Rodella S. "Assessing pain in hospital in-patients: a cross-sectional study in Tuscany, Italy". Internal and Emergency Medicine, 7(5), 477-482, 2012.
  • Accusoft Corporation. “Form Processing”. https://www.accusoft.com/type/forms-processing (26.04.2015).
  • Bergeron B. "Clinical data capture: OMR and OCR and your flatbed scanner". Medscape General Medicine, 7(2), 66-71, 2005.
  • Di Ruberto C. “Recognition of shapes by attributed skeletal graphs”. Pattern Recognition, 37(1), 21-31, 2004.
  • Jain T, Tewari A, Akash E. “Computer Vision Based OMR Sheet Evaluation Using OPENCV". Challenges & Opportunities for Technological Innovation in India, Luckow, India, 16.04.2013.
  • Zampirolli FA, Gonzalez JAQ, Neves. “Automatic correction of multiple-choice tests using digital cameras and image processing”. IX Workshop de Visão Computacional, Rio de Janeiro, Brazil, 03-05 June 2013.
  • Dell N, Breit N, Chaluco T, Crawford J, Borriello G. “Digitizing paper forms with mobile imaging technologies”. 2nd ACM Symposium on Computing for Development, Atlanta, GA, USA, 10-11 March 2012.
  • Parikh T, Javid P, Ghosh K, Sasikumar K, Toyama K. “Mobile phones and paper documents: evaluating a new approach for capturing microfinance data in rural India”. Conference on Human Factors in Computing Systems, Montreal, Quebec, Canada, 22-27 April 2006.
  • OpenCV. Open Source Computer Vision. “Image Processing Library for Android Platform”. http://opencv.org/platforms/android.html (26.04.2015)
  • Gordon R. Essential JNI: Java Native Interface. Upper Saddle River, NJ, USA, Prentice Hall,1998.
  • Vaish R, Ishikawa ST, Liu, J, Berkey SC, Strong P, Davis, J. “Digitization of health records in rural villages”. IEEE Global Humanitarian Technology Conference South Asia Satellite, Trivandrum, India, 23-24 August 2013.
  • Kae A, Learned-Miller E. “Learning on the fly: Font-Free Approaches to Difficult OCR Problems”. 10th International Conference on Document Analysis and Recognition, Barcelona, Spain, 26-29 July 2009.
  • Bow ST. Pattern Recognition and Image Preprocessing. 2nd ed. New York, USA, CRC Press, 2002.
  • Gülbin A, Ekenel HK, Erçil A. "Gürbüz nesne tanima ve konum belirleme sistemi". 11. Sinyal İşleme ve İletişim Uygulamaları Kurultayı, İstanbul, Türkiye, 18-20 Haziran 2003.
  • Bay H, Ess A, Tuytelaars T, Van Gool L. “Speeded-Up robust features (SURF)”. Computer Vision and Image Understanding, 110(3), 346-359, 2008.
  • Lowe DG. “Distinctive image features from scale-invariant keypoints”. International Journal of Computer Vision, 60(2), 91-110, 2004.
  • Wynn R. “Optical mark recognition”. Data Processing, 26(9), 26-27, 1984.
  • Gonzalez RC, Woods RE, Eddins SL. Digital Image Processing Using MATLAB. 2nd ed. McGraw Hill Education, 2011.

Mobil tabanlı optik form değerlendirme sistemi

Year 2016, Volume 22, Issue 2, 94 - 99, 01.05.2016

Abstract

Ülkemizde ve dünyadaki eğitim sistemlerinde gerek öğrencilerin başarılarının değerlendirilmesinde gerekse öğrenci seçiminde çoktan seçmeli şıklar içeren optik formlar çok sık kullanılmaktadır. Optik formlar optik okuyucu cihazlar sayesinde optik işaret tanıma teknikleri kullanılarak değerlendirilmektedir. Bu tip cihazların pahalı olması, bu cihazlara erişimin sınırlı olması ve değerlendirme sonuçlarını bekleme süresinin uzun olması hem büyük şehirlerde hem de taşrada çalışan eğitimcilere zorluk çıkarmaktadır. Bu çalışmada eğitimcilerin sahip oldukları akıllı telefon ya da tabletleri aracılığı ile bir mekâna ya da optik cihaza bağlı kalmadan, hızlı bir şekilde öğrenci cevap formlarını değerlendirebilecekleri mobil bir yazılım geliştirilmiştir. Optik form tanıma, okuma ve değerlendirme işlemi eğitimcinin mobil telefonu ya da tableti aracılığı ile çektiği öğrencinin cevap formu görüntüsü üzerinde yapılmaktadır. Geliştirdiğimiz Android tabanlı mobil uygulama kullanıcı dostu bir arayüze sahip olup başarı oranı yüksektir ve bu alanda mobil ortamlarda çalışan ilk uygulama olma özelliğini taşımaktadır.

References

  • Monga H, Monga P, Kaur M. “A novel optical mark recognition technique based on biogeography based optimization”. International Journal of Information Technology and Knowledge Management, 5(2), 331-333, 2012.
  • Sen S, Bricka S. “Data collection technologies-past, present, and future”. 12th International Conference on Travel Behaviour Research, Jaipur, Rajasthan, India, 13-16 December 2009.
  • Syrex Corporation. “ICR, OCR and OMR - A Comparison of Technologies”. http://www.syrex.com.ph/Product/Download?filename =WhatIsOMR(26.04.2015).
  • Lucenteforte E, Collini F, Simonetti M, Messeri A, Caprilli S, Rasero L, Lapi F, Guidi G, Abeti MS, Mugelli A, Rodella S. "Assessing pain in hospital in-patients: a cross-sectional study in Tuscany, Italy". Internal and Emergency Medicine, 7(5), 477-482, 2012.
  • Accusoft Corporation. “Form Processing”. https://www.accusoft.com/type/forms-processing (26.04.2015).
  • Bergeron B. "Clinical data capture: OMR and OCR and your flatbed scanner". Medscape General Medicine, 7(2), 66-71, 2005.
  • Di Ruberto C. “Recognition of shapes by attributed skeletal graphs”. Pattern Recognition, 37(1), 21-31, 2004.
  • Jain T, Tewari A, Akash E. “Computer Vision Based OMR Sheet Evaluation Using OPENCV". Challenges & Opportunities for Technological Innovation in India, Luckow, India, 16.04.2013.
  • Zampirolli FA, Gonzalez JAQ, Neves. “Automatic correction of multiple-choice tests using digital cameras and image processing”. IX Workshop de Visão Computacional, Rio de Janeiro, Brazil, 03-05 June 2013.
  • Dell N, Breit N, Chaluco T, Crawford J, Borriello G. “Digitizing paper forms with mobile imaging technologies”. 2nd ACM Symposium on Computing for Development, Atlanta, GA, USA, 10-11 March 2012.
  • Parikh T, Javid P, Ghosh K, Sasikumar K, Toyama K. “Mobile phones and paper documents: evaluating a new approach for capturing microfinance data in rural India”. Conference on Human Factors in Computing Systems, Montreal, Quebec, Canada, 22-27 April 2006.
  • OpenCV. Open Source Computer Vision. “Image Processing Library for Android Platform”. http://opencv.org/platforms/android.html (26.04.2015)
  • Gordon R. Essential JNI: Java Native Interface. Upper Saddle River, NJ, USA, Prentice Hall,1998.
  • Vaish R, Ishikawa ST, Liu, J, Berkey SC, Strong P, Davis, J. “Digitization of health records in rural villages”. IEEE Global Humanitarian Technology Conference South Asia Satellite, Trivandrum, India, 23-24 August 2013.
  • Kae A, Learned-Miller E. “Learning on the fly: Font-Free Approaches to Difficult OCR Problems”. 10th International Conference on Document Analysis and Recognition, Barcelona, Spain, 26-29 July 2009.
  • Bow ST. Pattern Recognition and Image Preprocessing. 2nd ed. New York, USA, CRC Press, 2002.
  • Gülbin A, Ekenel HK, Erçil A. "Gürbüz nesne tanima ve konum belirleme sistemi". 11. Sinyal İşleme ve İletişim Uygulamaları Kurultayı, İstanbul, Türkiye, 18-20 Haziran 2003.
  • Bay H, Ess A, Tuytelaars T, Van Gool L. “Speeded-Up robust features (SURF)”. Computer Vision and Image Understanding, 110(3), 346-359, 2008.
  • Lowe DG. “Distinctive image features from scale-invariant keypoints”. International Journal of Computer Vision, 60(2), 91-110, 2004.
  • Wynn R. “Optical mark recognition”. Data Processing, 26(9), 26-27, 1984.
  • Gonzalez RC, Woods RE, Eddins SL. Digital Image Processing Using MATLAB. 2nd ed. McGraw Hill Education, 2011.

Details

Primary Language English
Journal Section Research Article
Authors

Asım Sinan YÜKSEL>

0000-0003-1986-5269


İbrahim Arda ÇANKAYA This is me


Mehmet Ali YALÇINKAYA This is me


Nurullah ATEŞ This is me

Publication Date May 1, 2016
Published in Issue Year 2016, Volume 22, Issue 2

Cite

Bibtex @ { pajes219178, journal = {Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {1300-7009}, eissn = {2147-5881}, address = {}, publisher = {Pamukkale University}, year = {2016}, volume = {22}, number = {2}, pages = {94 - 99}, title = {Mobile based optical form evaluation system}, key = {cite}, author = {Yüksel, Asım Sinan and Çankaya, İbrahim Arda and Yalçınkaya, Mehmet Ali and Ateş, Nurullah} }
APA Yüksel, A. S. , Çankaya, İ. A. , Yalçınkaya, M. A. & Ateş, N. (2016). Mobile based optical form evaluation system . Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi , 22 (2) , 94-99 . Retrieved from https://dergipark.org.tr/en/pub/pajes/issue/20566/219178
MLA Yüksel, A. S. , Çankaya, İ. A. , Yalçınkaya, M. A. , Ateş, N. "Mobile based optical form evaluation system" . Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 22 (2016 ): 94-99 <https://dergipark.org.tr/en/pub/pajes/issue/20566/219178>
Chicago Yüksel, A. S. , Çankaya, İ. A. , Yalçınkaya, M. A. , Ateş, N. "Mobile based optical form evaluation system". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 22 (2016 ): 94-99
RIS TY - JOUR T1 - Mobile based optical form evaluation system AU - Asım Sinan Yüksel , İbrahim Arda Çankaya , Mehmet Ali Yalçınkaya , Nurullah Ateş Y1 - 2016 PY - 2016 N1 - DO - T2 - Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi JF - Journal JO - JOR SP - 94 EP - 99 VL - 22 IS - 2 SN - 1300-7009-2147-5881 M3 - UR - Y2 - 2022 ER -
EndNote %0 Pamukkale University Journal of Engineering Sciences Mobile based optical form evaluation system %A Asım Sinan Yüksel , İbrahim Arda Çankaya , Mehmet Ali Yalçınkaya , Nurullah Ateş %T Mobile based optical form evaluation system %D 2016 %J Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi %P 1300-7009-2147-5881 %V 22 %N 2 %R %U
ISNAD Yüksel, Asım Sinan , Çankaya, İbrahim Arda , Yalçınkaya, Mehmet Ali , Ateş, Nurullah . "Mobile based optical form evaluation system". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 22 / 2 (May 2016): 94-99 .
AMA Yüksel A. S. , Çankaya İ. A. , Yalçınkaya M. A. , Ateş N. Mobile based optical form evaluation system. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2016; 22(2): 94-99.
Vancouver Yüksel A. S. , Çankaya İ. A. , Yalçınkaya M. A. , Ateş N. Mobile based optical form evaluation system. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2016; 22(2): 94-99.
IEEE A. S. Yüksel , İ. A. Çankaya , M. A. Yalçınkaya and N. Ateş , "Mobile based optical form evaluation system", Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 22, no. 2, pp. 94-99, May. 2016

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