Some Concerns on the Measurement for Biometric Analysis and Applications
Patrick S. P. Wang · Series in machine perception and artificial intelligence · 2007
Some concerns of measurement for biometric analysis and synthesis are investigated. This research tries to reexamine the nature of the basic definition of “measurement ” of distance between two objects or image patterns, which is essential for comparing the “similarity ” of patterns. According to a recent International Workshop on Biometric Technologies: Modeling and Simulation at University of Calgary, Canada [Yanushkevich et al., Eds. (2004)], biometric refers to the studies of analysis, synthesis, modeling and simulation of human behavior by computers, including mainly recognition of hand printed words, machines printed characters, handwriting, fingerprint, signature, facial expression, speech, voice, emotion and iris etc. The key idea is the “measurement ” that defines the similarity between different input data that can be represented by image data. This paper deals with the very fundamental phenomena of “measurement ” of these studies and analysis. Preliminary findings and observations show that the concepts of “segmentation ” and “disambiguation ” are extremely important, which have been long ignored. Even while computer and information professionals and researchers have spent much effort, energy, and time, trying very hard and diligently to develop methods that may reach as high as 99.9999 % accuracy rate for character and symbol recognition, a poorly or ill considered pre-designed board poster or input pattern could easily destroy its effectiveness and lower the overall performance accurate rate to less than 50%. The more data it handles, the worse the results. Its overall performance accuracy rate will be proportionally decreasing. Take