The book "Case-Based Reasoning on Images and Signals" offers a comprehensive examination of the application of case-based reasoning (CBR) in signal and image processing. It is the first of its kind to specifically address the integration of CBR strategies into systems for signal interpretation. At a time when signal processing systems are gaining increasing importance in fields such as medicine, industry, and biotechnology, this specialized book tackles the challenges associated with existing statistical and knowledge-based techniques. These techniques often exhibit shortcomings in terms of robustness, accuracy, and adaptability. The book presents new approaches that enable adaptation to changing environmental conditions and user needs. It covers the various phases of the signal processing process and provides insights into the development of systems capable of extracting high-quality information from signals. The topics discussed include both one-dimensional and multidimensional signal interpretations and the associated requirements for data representation and similarity measurement.