AFIS data compression

Abstract

This article describes the development and implementation of a data compression algorithm designed specifically for fingerprints, referred to as GBP compression. The algorithm is herein discussed. Data Compression algorithms can be designed for general applications, meaning the input data is unknown. This is more commonly referred to as generic data. [LI01] Or, data compression algorithms can be designed for specific applications. e.g. AFIS [Automated Fingerprint Identification Systems] "When the input is known, higher compression ratios can be achieved with the knowledge of the input data stream." To-date, the highest compression ratio for an unknown input data stream, for all data compression algorithms, is JPEG with an average compression ratio range of 1:17 -- 1:23. [PEN03] The algorithm herein discussed, has a compression ratio range of 1:68 -- 1:92. There is a value, time and place for each design method - generic or specific - depending upon a variety of factors. Due to the nature of the use of AFIS for law enforcement and incrimination as well as criminal conviction, there are social issues that make data integrity of paramount concern. This factor influences algorithm selection and design. A lossless algorithm is a must! Also, the nature of AFIS is such that it operates across borders and between states, municipalities and jurisdictions. In addition to the usual issues and resistance to accepting new technology, including software [e.g. resistance to change, fear of system failure, etc.], there are the issues of changing engineering standards [hardware and software] which are governmentally determined as well as governmental policy decisions. Likewise, the portability required in implementing a new algorithm, will have to deal with a variety of hardware and software; as well as be designed to integrate into existing systems. This integration must include the ability to incorporate existing JPEG data files, from existing police databases. This requires a handshaking of standards and conversion programs that maintain data integrity. In addition, there is an in depth discussion of the limits of compression with a novel perspective.