Segmentation approach for offline handwritten Kannada scripts

Krupashankari S. Sandyal, Kiran Y. Chandrappa


India has more than 1,600 official languages, making it a multilingual country. Kannada, one of the major languages, originated in the state of Karnataka and is currently ranked 33rd among the accents that are most often spoken throughout the world. However, the survey shows that much more effort is needed to create a complete handwritten identification system. Segmentation is one of the crucial steps in a handwriting identification system that extracts significant objects from an image. The feature extraction and classification phases of handwritten text recognition will be more successful if the segmentation approaches selected are efficient. In the proposed system, segmentation was accomplished using bounding box and contour tracing methods. The result got is delivered to the next step of handwritten identification system. An average accuracy of 92.6% is worked out for line segmentation and word segmentation.


Feature extraction; Hough transform; Pre-processing; Recognition system; Segmentation

Full Text:




  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics