Images contain various types of useful information that should be extracted whenever required and this information may be in the form of text present in image. Extraction of this information involves detection, localization, extraction, enhancement and recognition of the text from the given image. Mathematical morphology is the foundation of morphological image processing, which consists of a s...

This paper studies the structure of vectors obtained by using term selection methods in high-dimensional text collection. We found that the distance to transition point (DTP) method omits commonly occurring terms, which are poor discriminators between documents, but which convey important information about a collection. Experimental results obtained on the Reuters-21578 collection with the k-NN...

Text embedded in image provides high-level semantic information for automatic annotation, indexing and retrieval. Text extraction involves detection, localization, extraction, enhancement and recognition of the text from the given image. However, variations of the text due to differences in size, style, orientation and alignment as well as low image contrast and complex background make the prob...

The systems currently available for content based image and video retrieval work without semantic knowledge, i.e. they use image processing methods to extract low level features of the data. The similarity obtained by these approaches does not always correspond to the similarity a human user would expect. A way to include more semantic knowledge into the indexing process is to use the text incl...

We describe a pc−based low cost visual system that can detect and extract text regions in visual signs in the scene and recognize them for location awareness. It employs a multi resolution image enhancement and segmentation methods based on symmetric neighborhood filter and hierarchical connected component analysis to extract written information on signboards which appears in the scene. The mul...

A probabilistic lattice chart parser is proposed for improving the performance of a text recognition technique. Digital images of words are recognized and alternatives for the identity of each are generated. Local word collocation statistics and a probabilistic chart parsing algorithm are used to determine the top N best parses for each sentence using the alternatives provided for the identity ...

Stripes are common sub-structures of text characters, and the scale of these stripes varies little within a word. This scale consistency thus provides us with a useful feature for text detection and segmentation. In this paper a new form of filter is derived from the Gabor filter, and it is shown this filter can efficiently estimate the scales of these stripes. The contrast of text in video can...

Thesaurus is one of the most important components for information retrieval (IR) systems. A thesaurus provides a precise and controlled vocabulary that serves to coordinate document indexing and retrieval then it improves the retrieval effectiveness. However the major problem with the manual thesaurus is a laborintensive task and therefore also expensive to build and hard to update in timely ma...

Abstract In our previous work, we have proved that the spatial coherence length (SCL) of the incident waves around the target together with the target configuration play a leading role in the determination of the enhancement in the radar cross-section (ERCS) of a target in a random medium. Owing to the double-passage effect, the ERCS is almost two when the SCL is much smaller or larger than the...

The field of off-line optical character recognition (OCR) has been a topic of intensive research for many years (Bozinovic, 1989; Bunke, 2003; Plamondon, 2000; Toselli, 2004). One of the first steps in the classical architecture of a text recognizer is preprocessing, where noise reduction and normalization take place. Many systems do not require a binarization step, so the images are maintained...