Direct Processing of Compressed Data
Shahram Latifi
Electrical and Computer Engineering Department, UNLV
Contact
Information
Shahram Latifi
Electrical and Computer Engineering Dept.
University of Nevada, Las Vegas
Las Vegas, NV 89154-4026
Phone: (702) 895-4016
Fax : (702) 895-4075
Email: latifi@ee.unlv.edu
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Keywords
ITU Group 3/4, Data Compression, Document Image Analysis, Image Processing.
Project
Summary
Progress in computer and communication technologies allows a large volume of digital information to be exchanged and archived. While the need for data compression is evident, many operations may have to be performed on the uncompressed data. This research investigates the following: (i) develop new algorithms for processing compressed data without fully decompressing them, (ii) develop new compression algorithms that allow given operations to be rapidly performed on compressed data, and (iii) use wavelet transforms for document image analysis, specifically document image segmentation.
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Project Impact
Goals,
Objectives, and Targeted Activities
Connected component extraction is an important operation in image processing.The problem of connected component extraction directly in the Group IV domain is being investigated. The idea is to detect the corner information existing in the Group IV domain and use this information to develop a new but faster algorithm. The second task being explored is the conversion of raster images into vector forms. This operation is of interest in many applications ranging from cartography to character recognition.
In the meantime, we have considered applying the emerging technology, wavelet transform, to document image processing. Most segmentations techniques rely on a priori knowledge or assumptions about the generic document layout structure and textual and graphical attributes. However, in many applications it is desirable to have segmentation methods that do not assume any a priori knowledge about document layout. Wavelet transforms have played an important role in classification of texture and abnormalities, and it is hoped they can be exploited efficiently in document image processing.
Project
References
Area
Background
Processing digital images has become widespread recently due to remarkable advances in hardware and software industry. Such images can be produced by converting photographs, printed text, and other media into digital form. Direct acquisition of data in digital form has also been desirable because of the reliability and precision involved in handling digital information.
The CCITT G3/G4 standard, developed based on run-length data, is widely accepted for binary document compression in general and facsimile transmission in particular. By means of this standard, users can interchange and share information efficiently and conveniently. This also leads to the desire to process the image to satisfy specific needs. Traditional algorithms for image processing are based on pixel, which are computationally expensive. This has motivated researchers to consider processing image data in the compression domain.
The algorithms for run-length-based coding schemes are well understood and proven to be efficient. In the CCITT G4 domain, white pass modes can be used to detect skew and image matching, while vertical modes can be searched for possible bar codes. Therefore one can see that the features and structures existing in coded data can be utilized and accessed directly to facilitate image operations.
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Potential
Related Projects
Data base operations could be done more efficiently if data were stored (perhaps in some sort of compressed form) and queried differently from the classic methods. Specific compression techniques may prove useful in improving performance of data intensive applications such as data mining.