iosr-JVSP   Volume-2 ~ Issue-6

ABSTRACT:Medical image segmentation plays an important role in one of the most challenging fields of engineering. Imaging modality provides detailed information about anatomy. It is also helpful in the finding of the disease and its progressive treatment. More research and work on it has enhanced more effectiveness as far as the subject is concerned. Different methods are used for medical image segmentation such as Clustering methods, Thresholding method, Classifier, Region Growing, Deformable Model, Markov Random Model etc. The main purpose of this survey is to provide a comprehensive reference source for the researchers involved in Expectation-Maximization based medical image processing. There are different types of Expectation-Maximization algorithms for medical image. Their advantages and disadvantages are discussed.

Keywords: Image segmentation, Medical Image Processing, Expectation-Maximization

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ABSTRACT:This paper lays emphasis on research that gives an insight to the auditory-tactile perception in electronic musical instruments (here, electronic violin) stating that most traditional musical instruments inherently convey tactile feedback to the performer along with the auditory feedback which leads to a tight performer-instrument relationship which is not found in electronic musical instruments. Hence, introducing the phenomenon of coupled perception of sound and vibration using digital signal processing in order to facilitate better auditory perception in electronic instruments. Thus the main objective of study is Audio-Driven Vibration Feedback for auditory perception by the violinists in an Electronic Violin. The expected results of the research project ((here electronic violin) are supposed to be claimed beneficial for introducing the phenomenon of coupled perception of sound and vibration in order to facilitate better auditory perception in electronic instruments.

Keywords: Amplitude modulation, Audio-Driven Vibration Feedback , Digital Signal Processing, Octave Shift, Vibrotactile.

[1] Mark T. Marshall, Marcelo M. Wanderley (Input Devices and Musical Interaction Laboratory McGill University - Music Technology), "Vibrotactile Feedback in Digital Musical Instruments" in proceedings of the 2006 International Conference on New Interfaces for Musical Expression (NIME06), Paris, France.

[2] Mark T. Marshall, Marcelo M. Wanderley "Examining the Effects of Embedded Vibrotactile Feedback on the Feel of a Digital Musical Instrument", Input Devices and Music Interaction Laboratory Centre for Interdisciplinary Research in Music Media and Technology McGill University – Montreal, QC, Canada

[3] M. E. Altinsoy, "Auditory-Tactile Interaction in Virtual Environments" (PhD Thesis, Shaker Verlag) (2006). N. Armstrong. "An Enactive Approach to Digital Musical Instrument Design." PhD thesis, Princeton University, Nov. 2006.

[4] M. E. Altinsoy, "Auditory-Tactile Interaction in Virtual Environments" (PhD Thesis, Shaker Verlag) (2006).

[5] Wollmana, C. Fritza and J. Frelatb, " Vibrotactile feedback in the left hand of violinists", in proceedings of the Acoustics 2012 Nantes Conference 23-27 April 2012, Nantes, France 3605.

[6] Sebastian Merchel and M. Ercan Altinsoy "Vibration in Music Perception" Presented the Audio Engineering Society, 134th Convention 2013 May 4-7, Rome, Italy

[7] Joseph Malloch, "Adding vibrotactile feedback to the T-stick digital musical instrument" Input Devices and Music Interaction Laboratory Centre for Interdisciplinary Research in Music Media and Technology McGill University – Montreal, QC, Canada

[8] Sebastian Merchel, M. Ercan Altinsoy and Maik Stamm, "Touch the Sound: Audio-Driven Tactile Feedback for Audio Mixing Applications", Chair of Communication Acoustics, Dresden University of Technology, Germany

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[10] D. Birnbaum and M. M.Wanderley. "A systematic approach to musical vibrotactile feedback." In Proceedings of the International Computer Music Conference '07 (ICMC'07), volume 2, page 397, Copenhagen, Denmark, 2007.

ABSTRACT: The RNS has been considered as an interesting area for researchers in recent year. This paper presents memoryless and area efficient RNS converters for moduli set with dynamic ranges up to 6n-bit. Residue number system (RNS) has mainly targeted parallelism and larger dynamic ranges. In this paper, we start from the moduli sets {2n, 2n - 1, 2n + 1, 2n – 2(n+1)/2 + 1, 2n + 2(n+1)/2 + 1} with dynamic range of 5n-bit and propose vertical extension in order to improve the parallelism and increase the dynamic range. The vertical extension increase the value of the power of 2 modulus in the five-moduli set. The Chinese remainder theorem is applied in this paper to derive an efficient reverse converter. This paper also proposed a conventional binary to RNS representation called RNS Forward conversion. The RNS forward converter is more efficient in terms of area, delay and power. Synthesis results suggest that the proposed vertical extension in RNS reverse converter allow reducing the area-delay product in comparison with the related state-of-the-art.

Keywords- Chinese Remainder theorem, Forward converter, Residue Number system, Reverse converter

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