R. Manoorubini

Bio: R. Manoorubini is an academic researcher from Shanmugha Arts, Science, Technology & Research Academy. The author has contributed to research in topics: Salt-and-pepper noise & Colors of noise. The author has an hindex of 1, co-authored 2 publications receiving 1 citations.

Enrichment of epigraphy using image processing

Abstract: The proposed work describes the difficulties during the conversion of inscription digitization, preservation and trifling dissimilarities among forefront and background. Basically the inscriptions were neither retained traditional size and nor the shape. Even though they doesn't have colour discrepancy linking foreground and background. In priviling technique describes the extractions in the inscription by using NGFICA method. Our method enhances the words and recognizes the characters alone. In proposing methodology the inscription that has been enhanced, recognized effortlessly.

Inhibition of acoustic noise using an adaptive LMS filter

Abstract: In an audio speech signal, acoustic noise is a common problem while the speech is processed. Here, we are going to create color noise and add with an audio signal, after that a model are introduced to eliminate that noise. This paper elaborates a new approach for noise cancellation in speech enhancement using an Adaptive LMS (Least Mean Square) filter and with the help of MATLAB Simulink we get the correct speech signal. This filter is used to remove the acoustic noise due to its simplicity in computation & robust behavior when implemented in finite-precision hardware. It provides better communication by suppressing the acoustic noise to a larger extent, since it provides a better balance between complexity & convergence speed. In spite of various methods, the results obtained in this way of noise cancellation are optimistic.

Preprocessing and Binarization of Inscription Images using Phase Based Features

Abstract: Epigraphs are important sources for reshaping our culture and history. They have a remarkable importance to mankind. But modern epigraphists find it difficult to interpret the information in scripts. It is mainly because inscriptions are eroded over a period of time due to natural calamities. Scripts of ancient times are largely unknown. Character sets used have changed from one form to another over the centuries. Therefore, for reading ancient scripts the characters have to be extracted. In this paper, a model for enhancement and binarization of historical epigraphs is proposed. This model consists phase congruency and of Gaussian model based background elimination using expectation maximization(EM) algorithm, preprocessing and binarization. In binarization, phase based features are used with specialised filters. Adaptive Gaussian filters are used to smoothen the output images. Weighted mean angle is calculated to differentiate the foreground from the background. EM algorithm removes the background noise completely where foreground characters are untouched. Proposed method is tested on different datasets of inscriptions and epigraphs. Obtained results are compared with the existing classical algorithms.