This introduces the Boise State Bangla Handwriting Dataset, a publicly accessible offline handwriting dataset of Bangla script. This can be found at https://scholarworks.boisestate.edu/saipl/1/
A basic character recognition method is presented where the features are extracted based on zonal pixel counts, structural strokes and grid points with U-SURF descriptors modeled with bag of features.
Benchmarking with this approach on 3 other publicly available Bangla datasets is reported. The highest classification accuracy obtained with an SVM classifier based on a cubic kernel is 96.8%.
© Nishatul Majid and Elisa H. Barney Smith, 2018.
Majid, Nishatul and Barney Smith, Elisa H.. (2018). "Introducing the Boise State Bangla Handwriting Dataset and an Efficient Offline Recognizer of Isolated Bangla Characters". The 16th International Conference on Frontiers in Handwriting Regocnition (ICFHR 2018), .