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Quality Metrics for Object-Based Data Mining Applications

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2 Author(s)
Mark Smith ; Southern Methodist University, Dallas, Texas ; Alireza Khotanzad

A new quality measurement for video sequences utilized in video retrieval systems and visual data mining applications is proposed. First, each frame of the sequence undergoes a segmentation step using extracted texture features from the gray-level cooccurrence matrix (GLCM) (Davis and Johns, 1979). Next, corresponding objects between adjacent frames are matched thus resulting in a 3-dimensional segmentation of the video into objects. Finally, color and texture features are extracted for each object in the sequence and provide the primary input in computing the quality measurement pertaining to the video. A low quality measurement may thus eliminate the possibility of the sequence being stored in a database retrieval system. The algorithm is tested on various types of video segments - pans, zooms, close-ups, and multiple objects' motion - with results included

Published in:

Information Technology, 2007. ITNG '07. Fourth International Conference on

Date of Conference:

2-4 April 2007