Digital Signal Processing

Anurag A. Ballewar ¹, S. D. Lokhande ¹

Affiliations
1 Department of Electronics & Telecommunication, Sinhgad College of Engineering, Pune (MH), IN

Abstract

The sound observed by physician from chest cavity consists of mixed lung and heart sound. They observe the changes in sound for detection of abnormality. Now a day's digital stethoscope is used in hospitals for patients monitoring. Its waveform is mixed with ambient noise and overlapped by vibrations from movement of body. The Fast ICA (independent component analysis) is source division procedure known as blind source separation technique. It is iterative and capable of dividing heart and lung sound giving physically important sources whenever physical mixing of two or more independent sources takes place. Noise reduction will be the very important initial stage in this algorithm as raw captured data contains most of the surface contact noise between stethoscope and chest surface. This algorithm will function as sound extractor from mixed heart and lung sound for its advanced examination which can be utilized to perceive diseases.

Keywords

Blind Source Separation, Lung Sound, Heart Sound, Auscultation, Independent Component Analysis.

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Moha Patil ¹, S. D. Lokhande ²

Affiliations
1 Sou. Venutai Chavan Polytechnic, Pune, IN
2 Sinhgad College of Engineering, Pune, IN

Abstract

Inpainting is the art of modifying an image in a form that is not detectable by an ordinary observer. There are numerous and different approaches to tackle the Inpainting problem. This paper demonstrates Criminisi's algorithm for removing large objects from digital images and filling the hole left behind. The Inpainting technique can be classified into two categories: (1) texture oriented and (2) structure oriented. Both the technique have their advantages and disadvantages. The Criminisi's algorithm demonstrated in this paper combines the advantages of both of these approaches. Exemplar based structure synthesis contains the essential process to replicate both texture and structure. A number of examples on real and synthetic images demonstrate the effectiveness of the algorithm.

Keywords

Object Removal, Image Inpainting, Texture Synthesis, Patch Propagation.

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Sneha S. Pathade ¹, S. D. Lokhande ¹, M. R. Bachute ²

Affiliations
1 Sinhgad College of Engineering, Pune, IN
2 G.H.R.I.E.T, Pune, IN

Abstract

In many application of noise cancellation, the changes in signal characteristics could be quite fast. This requires the utilization of adaptive algorithms, which converge rapidly. Least Mean Squares (LMS) and Recursive Least square (RLS) adaptive filters have been used in a wide range of signal processing application because of its simplicity in computation and implementation. Unfortunately, practical implementations of the algorithm are often associated with high computational complexity and/or poor numerical properties. In this describes a new approach for noise cancellation in speech enhancement using the two new adaptive filtering algorithms for attenuating noise in speech signals. Three performance criteria are utilized in this study: minimum step size, the minimum mean squared error (MSE), and the required filter order. The simulation results demonstrate the good performance of the LMS, RLS, and filtered-X LMS algorithm for active noise cancellation. After simulation in MATLAB the filtered-X algorithm is implemented on the TMS320C6713 processor to see the performance by use of speaker.

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