Due to usefitlness in recognition and identification biometric systems have become a major part of research. Paper proposes a multimodal biometric system using face modality combined with palm print and palm vein modality. The proposed methodology uses Local Statistical method in which pre-defined block of DCT coefficient were used to calculate standard deviation and store them as feature vector. Matching is done using distance between foature vector of testing and training data set. Results show that the Genuine Acceptance Rate (GAR) of foature level fusion is J 00% which is better than, that of uni-modal systems, hence having multimodality is advantageous. For testing and training database of J 00 students of College of Engineering Pune.
Ductile cast iron is preferred as nodular iron or spheroidal graphite iron. Ductile cast iron contains graphite in form of discrete nodules and matrix of ferrite and perlite. In order to determine the mechanical properties, one needs to determine volume of phases in matrix and nodularity in the microstructure of metal sample. Manual methods available for this, are time consuming and accuracy depends on expertize. The paper proposes a novel method for automatic quantitative analysis of microstructure of Ferritic Pearlitic Ductile Iron which calculates volume of phases and nodularity of that sample. This gives results within a very short time (approximately 5 sec) with 98% accuracy for volume phases of matrices and 90% of accuracy for nodule detection and analysis which are in the range of standard specified for SG 500/7 and validated by metallurgist.
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