Pattern Matching in Compressed Texts and Images surveys and appraises techniques for pattern matching in compressed text and images. Normally compressed data needs to be decompressed before it is processed. If however 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. It includes algorithms that are suitable for pattern matching for various compression methods, and compression methods designed specifically for pattern matching. This monograph provides a survey of this work while also identifying the important relationship between pattern matching and compression, and proposing some performance measures for compressed pattern matching algorithms. Pattern Matching in Compressed Texts and Images is an excellent reference text for anyone who has an interest in the problem of searching compressed text and images. It concludes with a particularly insightful section on the ideas and research directions that are likely to occupy researchers in this field in the short and long term.