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This Degree Project is carried through in association with Fototext in Guthenburg. The firmsees benefits using”Soft Proof” technology for both economic and time-saving. The reasonfor ”Soft Proofing” for internal/ external production is to estimate and controll documentswithout using digital or chemical printing output.The different technical solutions to ”Soft Proof”, knowledges and facts aboutColorManagement together with PDF-workflow is going to pattern for a correct succesfull”Soft Proofing” on the monitor.Acrobat 5 in association with Photoshop 6 are effectively used in ”Soft Proofing” technic.The advance and capacity of the graphical softwares which are explained in this reporthelps the users to begin to experiment with ”Soft Proof”. Graphical firms which are interestedto begin working with ”Soft Proof” need to allready have knowledge in ICC-profilingand a practical ColorManaged workflow.

Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.