Underground installations are networks of metal pipes and cables in space at a certain distance from the ground surface. Insulating layers of metal pipes of underground installations (gas, plumbing, electrical...) do not provide their full protection against corrosion and breakdowns. In urban areas, wandering currents (electric rail or earthing of power plants) repeatedly increase failures in underground installations in the environment. That is why a certain kind of protection is foreseen for the protection of metal pipes of underground installations against corrosion and destruction from wandering currents. However, until today there is no universal method for calculating the parameters of stationary and quasi-stationary electric fields of wandering currents and a general solution for arbitrary configuration, but it is possible to form a model algorithm for controlling the state and failures of insulation of underground electrical installations. Solutions for wandering currents could be determined by the criterion of similarity to transient currents on power lines. In the paper, in program MATLAB Simulink a simulation for the correction of wandering currents using foreign grounding has been performed on certain parts of underground installations. It has been shown that the solution of the task is possible with help of the model-algorythm which allows a determinaitn of the power on isolation layer of the cable sheat, and with simulation of the different versions of schedule of protective equipment, their optimal schedule could be determined.

An Eigen formulation is proposed for image quality assessment IQA. Each block is represented by an array composed of feature vectors (intensity/color at this stage). After attaching the complement feature(s), the auto-correlation matrix is computed for each block. The proposed full reference FR-IQA is simply the deviation of the Eigen values of the degraded image from that of the original image. Interestingly, the second largest Eigen value was sufficient to perform this comparison. Results and comparisons with SSIM and GMSD schemes on different types of degradation are demonstrated to show the effectiveness of the proposed schemes. Using TID2013 database, the proposed scheme outperforms SSIM. In addition, the proposed schemes is closer to the MOS score compared to GMSD; however, the correlation with MOS is inferior as illustrated in the tables. These results are concluded from the average behaviour on all the images using all degradations (with 5 levels) on the database.

Content-based image retrieval is the popular approach for image data searching because in this case, the searching process analyses the actual contents of the image rather than the metadata associated with the image. It is not clear from prior research which feature or which similarity measure performs better among the many available alternatives as well as what are the best combinations of them in content-based image retrieval. We performed a systematic and comprehensive evaluation of several visual feature extraction methods as well as several similarity measurement methods for this case. A feature vector is created after color and/or texture and/or shape features extraction. Then similar images are retrieved using different similarity measures. From experimental results, we found that color moment and wavelet packet entropy features are most effective whereas color autocorrelogram, wavelet moment, and invariant moment features show narrow result. As a similarity measure, cosine and correlation measures are robust in maximum cases; Standardized L2 in few cases and on average, city block measure retrieves more similar images whereas L1 and Mahalanobis measures are less effective in maximum cases. This is the first such system to be informed by a rigorous comparative analysis of the total six features and twelve similarity measures.

Digital image enhancement is a technique to process a digital image to improve the overall visual quality of image. In this paper, Variance concept based clipping threshold value is computed from input image pixel intensity to limit the rate of over enhancement. The histogram of the original image is sub-divided into five adjacent sections and the boundary values between adjacent sections are put from the penile value of intensity range. Besides, over enhancement of the image is avoided by clipping certain number of pixels having more intensity than the clipping limit and these pixels are rearranged below the clipping limit. The present method offers two advantages viz., clipping of the certain pixels based on the property of the data set itself. The another one is to histogram processing by parts and this has given better visual quality, low computation time with improved metrics related to image enhancement. Histogram of each specific sub-image is equalized independently and then combined to produce the final contrast enhanced image. The final output image is further processed through imreducehaze filter for more improve result. Quantitative evaluation of proposed algorithm is performed by CPCQI and QILV image quality metrics and the simulation results have shown that the proposed variance based histogram equalization algorithm produces better quality of image in terms of contrasts, brightness and color in comparison to the other existing histogram equalization algorithms.

This paper presents a design and implementation of Root Mean Square (RMS) measurement system based on fast discrete Wavelet using a dsPIC-type microcontroller. For data acquisition, two sensors have been used such as the voltage divider for sensing voltage and the Hall Effect sensor for sensing the current. The proposed method has the real-time calculation advantages and can be used in sinusoidal and non–sinusoidal electrical power systems. The results of calculations have been verified using MATLAB and Proteus ISIS simulations. It has been proved that the Wavelet transform measuring technique is more accurate as it takes in consideration all the harmonics in the analyzed signal and provides temporal information, which is absent in other transforms or not directly available in the Fourier transform.