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Mathematical Methods Of Statistics

Getting an efficient method of removing noise from the images, before processing them for further analysis is a great challenge for the researchers. Noise can degrade the image at the time of capturing or transmission of the image. Before applying image processing tools to an image, noise removal from the images is done at highest priority. Ample algorithms are available, but they have their own assumptions, merits and demerits. The kind of the noise removal algorithms to remove the noise depends on the type of noise present in the image. Best results are obtained if testing image model follows the assumptions and fail otherwise. In this paper, light is thrown on some important type of noise and a comparative analysis of noise removal techniques is done. This paper presents the results of applying different noise types to an image model and investigates the results of applying various noise reduction techniques.

A Comparative Study of Various Types of Image Noise and Efficient Noise Removal Techniques

With the increased usage of digital cameras and picture clicking devices, the number of digital images increases rapidly, which in return demand for image quality assessment in terms of blur. Based on the edge type and sharpness analysis using Laplacian operator, an effective representation of blur image detection scheme is proposed in this paper, which can determine that whether the image is blurred or not, and what is the extent of blur through Variance of Laplacian. In this project a simple, reliable and fast algorithm for image noise estimation is presented. Images taken for the testing is assumed to be corrupted by additive zero mean Gaussian noise. To exclude structures or details from contributive to the noise variance estimation, an easy edge detection algorithm inculcating first-order gradients is applied first. Then a Laplacian operator followed by an averaging over the whole image will provide very accurate noise variance estimation. There is only one parameter which is self-determined and adaptive to the image contents. Simulation results show that the proposed algorithm performs well for different types of images over a large range of noise variances. Performance comparisons against alternative approaches are also provided. Results obtain through screenshots of the experiments demonstrate the effectiveness of the proposed scheme.

Blur image detection using Laplacian operator and Open-CV

Background/Objectives: Digital image processing is used various fields for analyzing different applications such as medical sciences, biological sciences. Various image types have been used to detect plant diseases. This work is analyzed and compared two types of images such as Grayscale, RGB images and the comparative result is given. Methods/Statistical Analysis: We examined and analyzed the Grayscale and RGB images using image techniques such as pre processing, segmentation, clustering for detecting leaves diseases. Results/Finding: In detecting the infected leaves, color becomes an important feature to identify the disease intensity. We have considered Grayscale and RGB images and used median filter for image enhancement and segmentation for extraction of the diseased portion which are used to identify the disease level. Conclusion: RGB image has given better clarity and noise free image which is suitable for infected leaf detection than Grayscale image.

Implementation of RGB and Grayscale Images in Plant Leaves Disease Detection - Comparative Study

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications.

https://www.mdpi.com/1424-8220/17/2/286/pdf

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study.

Image processing is basically the use of computer algorithms to perform image processing on digital images. Digital image processing is a part of digital signal processing. Digital image processing has many significant advantages over analog image processing. Image processing allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and signal distortion during processing of images. Wavelet transforms have become a very powerful tool for de-noising an image. One of the most popular methods is wiener filter. In this work four types of noise (Gaussian noise , Salt & Pepper noise, Speckle noise and Poisson noise) is used and image de-noising performed for different noise by Mean filter, Median filter and Wiener filter . Further results have been compared for all noises.

/pdf/image-de-noising-by-various-filters-for-different-noise-34jttopyw3.pdf

Image De-noising by Various Filters for Different Noise

Magnetic properties of Co/CoO/Co polycrystalline film have been investigated in situ using the magneto-optic Kerr (MOKE) effect during growth of the sample and ex situ using superconducting quantum interference device measurements. Magnetic anisotropy with easy axis perpendicular to the film surface has been observed in the top Co layer, whereas the bottom layer was found to be soft with in-plane magnetization. Ex situ in-plane and out-of-plane diffraction measurements revealed that the growth of Co on oxidized interface takes place with preferential orientation of hcp c-axis perpendicular to the film plane, which results in the observed perpendicular magnetic anisotropy. Texturing of the c-axis is expected to be a result of minimization of the interface energy due to hybridization between Co and oxygen at the interface.

https://iopscience.iop.org/article/10.1088/0022-3727/47/10/105002/pdf

Interface induced perpendicular magnetic anisotropy in a Co/CoO/Co thin-film structure: an in situ MOKE investigation

In today's internet world, information can be search easily. There are verities of search engines present now a day's who gives information into some milliseconds. As information is easily available security of this information is a big issue. K-anonymity is one of the popular privacy preserving data publishing technique, which uses generalization technique. Generalization gives better data protection but leads loss of corelations among attribute. In some cases it fails to protect against membership disclosure. When in a dataset single attributes shows corelations with multiple attributes, then it becomes a big security and utility issue. In this paper we proposed K-AMOA Model who overcomes these drawbacks and provide better data utility for multiple overlapped attributes.

K-AMOA: K-Anonymity Model for Multiple Overlapped Attributes

Co film of 13 nm thickness has been deposited on native oxide (CoO) layer using electron beam evaporation technique. CoO (fcc) of 2.3 nm thickness has been prepared by oxidizing surface of 50 nm thick Co (fcc) by thermal annealing. The structure of the sample has been investigated in detail using in-plane and out-of-plane energy dispersive grazing incidence x-ray diffraction (GIXRD) at EDXRD beamline, Indus-2, RRCAT, Indore. It is found that the growth of the Co film takes place with preferential orientation of c-axis perpendicular to the film plane, which results in structure induced magnetic anisotropy with easy axis normal to the film plane.

Textured growth of Co film on CoO (fcc) layer; Structural studies using EDXRD beamline at Indus-2

In this paper, the problem of dynamic multicast routing in mobile ad hoc networks is investigated. Dynamic multicast routing has become a major issue in Manet. Mobile ad hoc networks (MANETs) are collection of wireless mobile nodes, thus connectivity is an issue in this network. Moreover it, the network topology is defined by its routing strategy. In MANET, the network topology keeps changing due to its inherent characteristics such as node mobility. Mobility is the main factor affecting topology changes and route formation. Routing algorithms are responsible for discovering routes between source and destination, in independent mobility environment. Furthermore, this kind of network organization performance is an essential issue. In the previous algorithm [1] the multi-casting tree is improved by using genetic algorithm based high-low mutation genetic algorithm. The proposed algorithm (hybrid algorithm), extension of the previously available algorithm (High low hyper mutation genetic algorithm) is implemented using the network simulator 3 environment. Hybrid algorithm is a mixture of genetic algorithm and K-nearest neighbor algorithm. Then hybrid algorithm compares with traditional algorithm using various performance parameters like throughput, packet delivery ratio, packet drop ratio, end to end delay. General Terms Mobility, dynamic multicast routing problem, genetic and kNearest Neighbour algorithm, hyper mutation based genetic algorithm.

/pdf/implementation-of-hybrid-algorithm-for-mobility-and-routing-wox5cw81ay.pdf

Pawan Patidar

Papers

Image De-noising by Various Filters for Different Noise

Interface induced perpendicular magnetic anisotropy in a Co/CoO/Co thin-film structure: an in situ MOKE investigation

K-AMOA: K-Anonymity Model for Multiple Overlapped Attributes

Textured growth of Co film on CoO (fcc) layer; Structural studies using EDXRD beamline at Indus-2

Implementation of Hybrid Algorithm for Mobility and Routing Issues in MANET