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In this paper, we have proposed personal multimodal biometric authentication system based on face detection, recognition and speaker verification for smart-phone environment. Proposed system detect the face with Modified Census Transform algorithm then find the eye position in the face by using gabor filter and  -means algorithm. Perform preprocessing on the detected face and eye position, then we recognize with Linear Discriminant Analysis algorithm. Afterward in speaker verification process, we extract the feature from the end point of the speech data and Mel Frequency Cepstral Coefficient. We verified the speaker through Dynamic Time Warping algorithm because the speech feature changes in real-time. The proposed multimodal biometric system is to fuse the face and speech feature (to optimize the internal operation by integer representation) for smart-phone based real-time face detection, recognition and speaker verification. As mentioned the multimodal biometric system could form the reliable system by estimating the reasonable performance.

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Breast cancer is a cancer which occurs commonly for women of the entire world.[9] In this thesis, in order to find cancer by using image conformation technology, computer tomography (CT), positron emission tomography (PET) and magnetic resonance imaging (MRI) images were used. For conforming the images of each the different modalities, surface points, which become common feature of MRI and CT images were extracted and they were registered in 3D by using iterative closet point. (ICP)

In this paper, we explore the PET