As vast amount of digital image data is getting archived by the advanced libraries, there is a requirement for an ef cient search methodologies to make them accessible according to client's data requirement. For their retrieval, it is imperative to recognize their contents. Current technologies for optical character recognition (OCR) and document analysis do not handle such documents adequately because of the recognition errors. Due to these challenges, computer is unable to recognize the characters while reading them. In this paper, we propose and effective word image matching scheme that achieves high performance in the presence of noise in image, degradation and word form-variants. Initially, each image in image-database is pre-processed. In the next step find contour method is used to detect blobs which are further passed in tesseract engine. Tesseract segments the characters from the image and stores in character database. Each word in the database is used to index a given set of images. During retrieval, the query word presented to the system is matched with characters in the database and all images containing instances of the query word are retrieved and presented to the user. Using this approach, our method is able to successfully handle images with different font styles, size and heavily touching characters. From the experimental results on the variety of image database it is observed that the extraction of text from the images is mostly accurate and indexing of words based on the position is working perfectly
