Segmentation Based Word Spotting Method for Handwritten Documents

Abstract

In this paper, we present a segmentation based word spotting method for handwritten document images using Co-occurrence Histograms of Oriented Gradients (Co-HOG) descriptor. The drawback of Histogram of Oriented Gradients (HOG) is that HOG ignores spatial information of adjacent pixels where as the Co-HOG take into account spatial contextual information by capturing the co-occurrence of orientation pairs of neighbouring pixels. In order to construct Co-HOG descriptor for word spotting, we divide a word image into blocks and Co-HOG features are extracted from each block and finally concatenate them to form a feature descriptor. The proposed method is evaluated using precision and recall metrics through experimentation conducted on popular GW dataset and confirmed that our method outperforms for this dataset.