Pattern Matching in Compressed Texts and Images

This review provides a survey of techniques for pattern matching in compressed text and images. Normally compressed data needs to be decompressed before it is processed, but if the compression has been done in the right way, it is often possible to search the data without having to decompress it, or at least only partially decompress it. The problem can be divided into lossless and lossy compression methods, and then in each of these cases the pattern matching can be either exact or inexact. Much work has been reported in the literature on techniques for all of these cases, including algorithms that are suitable for pattern matching for various compression methods, and compression methods designed specifically for pattern matching. This work is surveyed in this review. The review also exposes the important relationship between pattern matching and compression, and proposes some performance measures for compressed pattern matching algorithms. Ideas and directions for future work are also described.