By Khalid Saeed, Jerzy Pejas, Romuald Mosdorf
This e-book includes over 30 articles by means of recognized scientists/engineers reflecting the most recent advancements in complicated desktops and their purposes inside of Biometrics, info expertise safety and synthetic Intelligence.
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Additional resources for Biometrics, Computer Security Systems and Artificial Intelligence Applications
It was tested 4900 expressing of audio and audio-visual speech. Researches were made for different degree of disturbance of signal audio (Signal to Noise Ratio, SNR = 0, 5, 10, 20 dB). It was accepted, that for SNR = 20 dB signal audio is clean. It was accepted, that signal of video is clean for different SNR of audio. All three method of fusion signals of audio and video were tested. Tab. 5. shows results of third experiment. Fig. 6. shows level of mistakes of recognizing of audio speech and audio-visual speech.
Fig. 2. Examples of face detection with use of property of skin's color First, face of speaking person is detected. Before detection, one should to reduce the image size to 160 x 120, keeping the aspect ratio. The image is spreaded on three components RGB. Component B is subtracted from component R and area of color of Method of Speech Recognition and Speaker Identification Using Audio-Visual of Polish Speech and Hidden Markov Models 49 human skin is received . Then, a mask is put on in aim of qualification of face's area (see Fig.
Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafher, D. Lee, D. Petkovic, D. Steele and P. Janker, "Query by Image and Video Content: the QBIC System," IEEE Computer 28(9):310-315,1995. 21. G. Ciocca, R. Schettini, "A Relevance Feedback Mechanism for Content- 35:605-632, 1999. 22. C. , "Surfimage: A Flexible Content-Based Image Retrieval System," in Proc. ACM Multimedia, 1998. 23. R. Bach, C, Fuller, A. Gupta, A. Hampapur, B. Horovitz, R. Humphrey and R. Jain, "The Virage Image Search Engine: an Open Framework for Image Management," in Proc.