Morphological approach to scene change detection and digital video storage and retrieval

With the abstraction of digital video as the corresponding binary video- a process which upon numerous subjective experimentation seems to preserve (most of the) intelligibility of video content- we can pursue a precise and analytic approach to (digital video storage and retrieval) algorithm design that are based upon geometrical (morphological) intuition. The foremost and tangible general benefit of such abstraction, however, is the immediate reductions of both data and computational complexities involved in implementing various algorithms and databases. The general paradigm presented may be utilized to address all issues pertaining to video library construction including visualization, optimum feedback query generation, object recognition, e.t.c., but the primary focus of attention in this paper are the ones pertaining to detection of fast (including presence of flashlights) and gradual scene changes (such as dissolves, fades, and various special effects such as wipes). Upon simulation we observed that we can achieve performances comparable to those of others with drastic reductions in both storage and computational complexities. Furthermore, since the conversion from grayscale to binary videos can be performed directly (with minimal additional computation) in the compressed domain by thresholding on the DCT DC coefficients themselves (or by using the contour information attached to MPEG4 formats), the algorithms presented herein are ideally suited for performing fast (on-the-fly) determinations of scene change, object recognition and/or tracking, and other more intelligent tasks traditionally requiring heavy demand on computational and/or storage complexities. The fast determinations may then be used on their own merits or can be used in conjunction or complementation with other higher-layer information in the future.