Gabor Wavelets Based Word Retrieval from Kannada Documents

In this paper, we propose a technique for word retrieval based on Gabor wavelets. Gabor wavelets are employed to capture directional energy features of the word image. A pre-processing step is performed in order to improve the quality of the document images, at the same time word segmentation is accomplished using 294 document images. As a result, a large dataset of 45000 words is generated for experimentation. Then, Gabor wavelets are used to represent the candidate word as well as a query word. Then cosine distance is used to measure the similarity between two words, based on it, relevance of the word is estimated by generating distance ranks. Then correctly matched words are selected at different distance thresholds such as 96%, 97%, 98% and 99%. The results achieved are encouraging in terms of average precision 81.25%, average recall 82.09% and F measure 84.53% at a threshold 97%.