Details

Autor(en) / Beteiligte

• Arora, Sandhya
• Jahirabadkar, Sunita
• Kulkarni, Anagha

Titel

GPU Approach for Handwritten Devanagari Document Binarization

Ist Teil von

• Smart Innovations in Communication and Computational Sciences, p.299-308

Ort / Verlag

Singapore: Springer Singapore

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The optical character recognition (OCR) is the process of converting scanned images of machine printed or handwritten text, numerals, letters, and symbols into a computer processable format such as ASCII. For creating OCR’s paperless application, a system of high speed and of better accuracy is required. Parallelization of algorithm using graphics processing unit (GPU) along with CPU can be used to speed up the processing. In GPU computing, the compute-intensive operations are performed on GPU while serial code still runs on CPU. Binarization is one of the most fundamental preprocessing techniques in the area of image processing and pattern recognition. This paper proposes an adaptive threshold binarization algorithm for GPU. The aim of this research work is to speed up binarization process that eventually will help to accelerate the processing of document recognition. The algorithm implementation is done using Compute Unified Device Architecture (CUDA) software interface by NVIDIA. An average speedup of 2× is achieved on GPU GeForce 210 having 16 CUDA cores and 1.2 compute level, over the serial implementation.