Application Of Median Filter Research Articles

Two-dimensional and pseudo three-dimensional visualisation of foreign objects in milk carton using ultrasonic tomography

This paper presents the development of two-dimensional and pseudo three-dimensional visualisation of foreign object in milk carton using ultrasonic tomography system. Mathematical modelling based on ultrasonic amplitude wave and correlation between ultrasonic projection distance and voltage sensor are elaborated in this paper. Physical hazard contaminants such as metal, plastic, wood and glass materials were placed in the milk. The forward problem and the inverse problem of image reconstruction technique have been discussed briefly. 2D images of the contaminants are reconstructed using Linear Back-Projection (LBP) and Convolution Back-Projection (CBP) with Hanning, Hamming and Ram-Lak filter. A median filter technique has been combined to the algorithms for filtering noise of reconstructed images. The results show that image reconstruction using CBP-Ram-Lak has significantly yield the best image reconstruction for most tested phantoms. The application of median filter with 20 × 20 matrix have obtained a better image quality as they achieved the best values of PSNR and SSIM compared to non-median filter with 13.2765 and 0.7318, respectively for pairs of metal A - glass B (phantom Y-2). Pseudo three-dimensional (3D) image reconstruction for the foreign object has been carried out to provide more sufficient monitoring process in milk cartons. The 3D images were constructed based on stacking the 2D slice images in z-axis. Thus, the exact location of the object in the milk carton can be exposed clearly from various viewing angles. The results indicate that the ultrasonic tomography imaging system promises to be a non-invasive tool in quality monitoring especially for the detection of foreign objects in milk carton.

ПРИМЕНЕНИЕ МЕДИАННЫХ ФИЛЬТРОВ ПРИ ОБРАБОТКЕ ЭКСПЕРИМЕНТАЛЬНЫХ ДАННЫХ ПО ДИНАМИКЕ КОЛЕБАНИЙ ПЛАВУЧИХ СООРУЖЕНИЙ РАЗЛИЧНЫХ ТИПОВ

The paper is devoted to the analysis of increasing the accuracy of the spectral characteristics obtained after processing experimental data of the vibrations of a physical model of the offshore drilling platform in the experimental tank. The increase in accuracy is provided by the recognition and correction of breakdowns and errors in the course of median filtering of vibration recordings of different positions of the platform relative to the propagation of waves in the tank and with different deepening of the platform support columns. The median filters are known to belong to nonlinear transformations; therefore, their characteristics are determined by the structure of their processing procedures. In this case, these are narrow-band, random oscillations with maximum spectra at wave frequencies, at fundamental frequency of the platform oscillation and harmonics, at frequencies that are multiple to the fundamental frequency. To use median filters in processing such signals, the amplitude-frequency characteristics of the median filter were determined as a function of the ratio of the characteristic period of oscillations to the equivalent filter base, i.e. to multiplying a number of points in the filter core by the discreteness of measurements. As a result, the condition for the effective application of median filtering in the processing of narrow-band random signals has been determined, which is used in analyzing the spectra of the processes under study. There are given characteristic examples of the spectra of angular oscillations (by roll and depth) of a semisubmersible platform with different drafts. It has been shown that at maximum draft, when the model is most stable, median filtering suppresses high-frequency noise components of the vibration spectra by 5-10 times and, at the same time, the main features of the spectra are not distorted, i.e. the main energy-carrying components are reproduced without visible distortion. In the other limiting case, with minimum platform draft, changes in the high-frequency part of the spectra are negligible due to increased intensity of angular oscillations. In this case, the oscillation spectra also reproduce the main features of dynamic processes. These data indicate the selective sensitivity of the median filter to the structure of the operating procedure and possibility of improving the accuracy of reproduction of spectral characteristics by suppressing the high-frequency noise components of a signal.

Shape based Object Retrieval Technique for Vehicular Spare Parts

Shape based object retrieval technique is an application used for the automatic retrieval of vehicular spare parts based on the input image, this application can be useful in the automobile industry/shop for the retrieval of specific object from the group of objects. For the retrieval process first the database has been designed to store different shapes of nuts that are hexagon and square. With the application of median filter and wiener filters in the preprocessing step, the canny edge-detector for identifying the edges and to ascertain shape of the input and database images the convex hull approach is applied. This system is successful in retrieving the shape of the images which already exist in the database and the method results with the accuracy of 82.1875%

Design and implementation of a new efficient median filtering algorithm

A new bit-level algorithm for median-type filters, based on the concept of majority, and a new hardware implementation suitable for VLSI implementation are introduced. The proposed structure has an area complexity of O(N(N+w)) and a time complexity of O(w). Compared with other existing algorithms, the new algorithm exhibits reduced hardware requirements and better processing speed. In addition, a new application of median filtering in electrocardiograms (ECG) is presented. The new method uses the concept of median filtering to restore the baseline of an ECG signal, which is, in most cases, unstable due to artifacts, e.g. a patient's movement or breathing.

Restoration of images from the scanning-tunneling microscope

During the acquisition of an image from any probe microscope instrument, various noise sources cause distortion in the observed image. It is often the case that impulsive disturbances cause bright groups of pixels to replace the actual image data in these locations. Furthermore, the images from a probe microscope show some amount of blurring caused both by the instrument function and the material properties. In almost all image-processing applications it is important to remove any impulsive distortion that may be present before deblurring can be attempted. We give a technique for detecting these impulses and reconstructing the image. This technique is superior to the standard global application of median filters for the case considered. The reconstruction is limited only to the affected regions and therefore results in a much sharper and more meaningful image. With the assumption of Gaussian blur it is then possible to propose several different deblurring methodologies. We present a novel Wiener-filter deblurring implementation and compare it to both maximum-entropy and Richardson-Lucy deblurring.

The enhancement of seismogram parameters using image processing techniques

The seismic parameters of instantaneous envelope, phase and frequency are sometimes of interest. While displaying those parameters is one objective, another is to study innovative display techniques which might quickly draw the eye or computer to a seismic feature. A thresholded and filled display called a “quadragram” is tried. Application of median filtering is shown to be quite useful.