Spatial Similarity Retrieval in Video Databases

✍ Scribed by Yung-Kuan Chan; Chin-Chen Chang

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 131 KB
• Volume: 12
• Category: Article
• ISSN: 1047-3203
• DOI: 10.1006/jvci.2000.0460

✦ Synopsis

A nine-direction lower-triangular (9DLT) matrix describes the relative spatial relationships among the objects in a symbolic image. In this paper, the 9DLT matrix will be transformed into a linear string, called 9DLT string. Based on the 9DLT string, two metrics of similarity in image matching measures, simpler but more precise, are provided to solve the subimage and similar image retrieval problems. Moreover, a common component binary tree (CCBT) structure will be refined to save a set of 9DLT strings. The revised CCBT structure not only eliminates the redundant information among those 9DLT strings, but also diminishes the processing time for determining the image matching distances between query frames and video frames. Experiments indicate that the storage space and the processing time are greatly reduced through the revised CCBT structure. A fast dynamic programming approach is also proposed to handle the problem of sequence matching between a query frame sequence and a video frame sequence.