Olarik Surinta, Artificial Intelligence and Cognitive Engineering (ALICE)

"Working at the frontiers of knowledge", RUG

Research institute: Artificial Intelligence and Cognitive Engineering (ALICE)
Research group: Autonomous Perceptive Systems (APS)
Expertise: Artificial Intelligence, Machine Learning, Pattern Recognition, Image Processing, Handwritten Character Recognition

Dissertation: Multi-Script Handwritten Character Recognition
         Using Feature Descriptors and Machine Learning

Research project: Multi-script handwritten character recognition using feature descriptors and machine learning
    There exists no generic method for recognizing handwritten scripts from different writing systems, cultures or historical periods. Asian scripts pose a number of interesting fundamental problems at the levels of image processing, text segmentation, feature extraction, shape classification and language modeling. Instead of spending human efforts at each of these level, the current challenge is to exploit machine learning methods. The main objective of the project is to automatically recognize handwritten Thai and to automatically convert documents written in Thai to text files.

Thai handwritten character MLS dataset, Moscow Archives, 1672

Supervisor

dr. M.A. (Marco) Wiering

dr. M.A. (Marco) Wiering

Website: ~mwiering

Video Lecture: Deep Support Vector Machines

Expertise: Machine Learning, Pattern Recognition, Data Mining, Neural Networks, Artificial Intelligence, Robotics, Computer Vision

Publications

  • P. Pawara, E. Okafor, O. Surinta, L.R.B. Schomaker and M.A. Wiering, "Comparing Local Descriptors and Bags of Visual Words to Deep Convolutional Neural Networks for Plant Recognition" in Pattern Recognition Applications and Methods (ICPRAM), The 6th International Conference on, 2017, (accepted). link slide pdf
  • E. Okafor, P. Pawara, F. Karaaba, O. Surinta, V. Codreanu, L.R.B. Schomaker and M.A. Wiering, "Comparative Study Between Deep Learning and Bag of Visual Words for Wild-Animal Recognition," in Computational Intelligence (SSCI), IEEE Symposium Series on, 2016, (accepted). link slide pdf
  • F. Karaaba, O. Surinta, L.R.B. Schomaker and M.A. Wiering, "Robust Face Identification with Small Sample Sizes using Bag of Words and Histogram of Oriented Gradients," in Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAAP), The 10th International Joint Conference on, 2016, pp. 582-589. link slide pdf
  • F. Karaaba, O. Surinta, L.R.B. Schomaker and M.A. Wiering, "Robust Face Recognition by Computing Distances From Multiple Histograms of Oriented Gradients," in Computational Intelligence in Biometrics and Identity Management (IEEE CIBIM), IEEE Symposium Series on, 2015, pp. 203-209. link slide pdf
  • O. Surinta, M.F. Karaaba, T.K. Mishra, L.R.B. Schomaker and M.A. Wiering, "Recognizing Handwritten Characters with Local Descriptors and Bags of Visual Words," in Engineering Applications of Neural Networks (EANN), The 16th International Conference on, 2015, pp. 255-264. link slide pdf
  • O. Surinta, M.F. Karaaba, L.R.B. Schomaker and M.A. Wiering, "Recognition of handwritten characters using local gradient feature descriptors," in Engineering Applications of Artificial Intelligence, (45)2015, pp. 405-414. link pdf
  • F. Karaaba, O. Surinta, L.R.B. Schomaker and M.A. Wiering, "In-Plane Rotational Alignment of Faces by Eye and Eye-Pair Detection," in Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAAP), The 10th International Joint Conference on, 2015, pp. 392-399. link poster pdf
  • V. Codreanu, B. Dröge, D. Williams, B. Yasar, P. Yang, B. Liu, F. Dong, O. Surinta, L.R.B Schomaker, J.B.T.M. Roerdink, and M.A. Wiering, "Evaluating automatically parallelized versions of the Suport Vector Machine", Concurrency and Computation: Practice and Experience, 2014, pp. 1-21. link pdf
  • O. Surinta, M. Holtkamp, M.F. Karaaba, JP. van Oosten, L.R.B. Schomaker and M.A. Wiering, "A* Path Planning for Line Segmentation of Handwritten Documents," in Frontiers in Handwriting Recognition (ICFHR), The 14th International Conference on, 2014. pp. 175-180. link poster pdf
  • O. Surinta, L.R.B. Schomaker, and M.A. Wiering, "A comparison of feature and pixel-based methods for recognizing handwritten Bangla digits," in Document Analysis and Recognition (ICDAR), The 12th International Conference on, 2013, pp. 165-169. link poster pdf
  • O. Surinta, L.R.B. Schomaker and M.A. Wiering, "Handwritten Character Classification Using the Hotspot Feature Extraction Technique," in Pattern Recognition Applications and Methods (ICPRAM), The 1st International Conference on , 2012. pp. 261-264. link poster pdf