A Novel Handwritten Urdu Word Spotting Based on Connected Components Analysis

We propose a novel word spotting system for Urdu words within handwritten text lines. Spatial information of diacritics is integrated to the detection of the main connected components in candidate words generation. An Urdu word recognition system is effectively designed and applied to classify the candidate words. In this word recognition system, compound features and SVM were adapted. The verification/rejection process was based on the outputs from the Urdu word recognition system and the image´s global features were applied to achieve a promising result. As a result, a high 92.11% correct segmentation rate, a 50.75% word spotting precision rate were achieved while maintaining a 70.1% recall on CENPARMI´s Urdu Database.