Image Watermarking Approach Using LSB and Laplacian Filter

With the growth of information technologies, E-industry safety has recently become the mutual attention of education and business firms. Digital image watermarking is a technique that refers to the security of multimedia data. It is a process referred to the security and authentication of a digital image, video, and audio by embedding a watermark. Watermarking technique applies a number of variable editions to the host content, where the addition is related to embed information. In the past, researchers develop multiple simple watermarking techniques, today race is to find a region where the watermark is imperceptible and have a high payload. In this paper, an invisible image watermarking technique based on the least significant bit (LSB) and laplacian filter is proposed. The original image is divided into blocks and the laplacian filter is applied on each block. Laplacian is a derivative filter that uses the second derivate to find out the area of rapid changes in the image and the least significant bit is a technique to embed a watermark into the bit positions. Watermark is embedded on these regions which is favourable in achieving high desirable properties. This technique shows strong robustness against image processing and geometrical attacks. In evaluation with state of art methods, the proposed technique shows satisfactory progress.

Comparison of closed loop performance of consistency process dynamics for various PID controller algorithms

In this work, various algorithms of PID (Proportional-Integral-Derivative) controllers such as series, parallel, series together with derivative filter and parallel together with derivative filter form are implemented for the comparative analysis of the closed loop responses of an important parameter in head box of a paper machine in a paper making process industry called consistency, which has FOPDT (First Order Plus Dead Time) dynamics. Also the comparison is made between the closed loop responses achieved from different values of derivative filter factor for non-ideal situations. The steady state and dynamic characteristics are analyzed and compared and important inferences are derived.

Multi Distance Face Recognition of Eye Localization with Modified Gaussian Derivative Filter

Face recognition at a distance (FRAD) is one of the most difficult types of face recognition applications, particularly at a distance. Due to the poor resolution of facial image, it is difficult to identify faces from a distance. Recently, while recording individuals, the camera view is broad and just a small portion of a person's face is visible in the image. To ensure that the facial image has a low resolution, which deteriorates both face detection and identification engines, the facial image is constantly at low resolution. As an immediate solution, employing a high-definition camera is considered as a simple and practical approach to improve the reliability of algorithm and perform well on low-resolution facial images. While facial detection will be somewhat decreased, a picture with higher quality will result in a slower face detection rate. The proposed work aims to recognize faces with good accuracy even at a distance. The eye localization works for the face and eye location in the face of a human being with varied sizes at multiple distances. This process is used to detect the face quickly with a comparatively high accuracy. The Gaussian derivative filter is used to reduce the feature size in the storage element, which improves the speed of the recognition ratio. Besides, the proposed work includes benchmark datasets to evaluate the recognition process. As a result, the proposed system has achieved a 93.24% average accuracy of face recognition.

Novel Application of Selfish Herd Optimisation Based Fractional Order Cascaded Controllers for AGC Study

This article deals with Automatic Generation Control (AGC) of a three-area power system having five diversified sources of generation like thermal unit, hydro unit, wind unit, diesel unit and a gas unit are interconnected together. Area-1 of the power system consists of a thermal, a hydro and a wind unit, area-2 has a thermal, a hydro and a diesel unit and area-3 consists of a thermal, a hydro and a gas unit. To make system more realistic different nonlinear components like governor dead band (GDB), generation rate constraint (GRC), Boiler dynamics and communication delay are taken into account. A novel two degree of freedom fractional order PID with derivative filter and fractional order PD with derivative filter (2-DOF-FOPIDN-FOPDN) cascaded control strategy is adopted to improve the dynamic performance of the power system. Results obtained with the proposed cascaded controller are compared with that of PID, FOPID and 2-DOF-PIDN-PDN cascaded controller to prove its superiority. To enumerate the gains of different controllers optimally, a recently developed bio-inspired optimisation algorithm named Selfish Herd Optimisation (SHO) is capitalised. Further, the work is extended by taking a two area hydro thermal system to compare the result of the SHO tuned PID controller with that of modern hybrid firefly algorithm-pattern search (hFA-PS) technique. Transient analysis is carried out by applying a sudden load disturbance of 0.01 p.u in area-1 and the robustness of the controller is examined by varying both system parameters and applying a randomly varying load in area-1. From the investigation it is concluded that the 2-DOF-FOPIDN-FOPDN controller gives a flawless and a distinct performance.

Geophysical Investigation of Babylon archeological City, Iraq

A geophysical survey was carried out at old archeological Babylon City, which is located 90.0 km to the south of Baghdad. Three geophysical methods were applied in this survey. The VES resistivity method, for soil conductivity and layering testing. GPR and magnetic methods, for detecting subsurface archeological bodies. The resistivity results showed values lower than 5.0 ohm. m, and subsurface distortion, which are probably related to buried archeological ruins. Due to the low electrical resistivity of the top soil, the GPR method did not reach a good penetrating depth. Wide range of frequencies, 30 MHz, 250 MHz, 500 MHz, and 100MHz were applied. The high signal attenuation of the top soil resulted in distorted radar-grams with faint shallow anomalies. The GPR survey was conducted at different seasons hoping that the dry conditions of the hot summer could change the top soil electrical resistivity. Nevertheless, few GPR radar- grams show point reflections that related to small dense bodies at depths of 0.8 – 2.0, which could be archeological bricks walls. The magnetic survey was carried out in two stages using Cesium magnetometer of high sensitivity. An area of 140.0 m x 240.0 m was surveyed at the first stage, which is covered by twenty-eight N-S traverses. The preliminary results show the effects of the N-S profiling, which can be removed by directional first derivative filter. It showed indications of subsurface archeological features. In the second stage, an area of 40.0 x 40.0 meters was chosen for detailed survey. The survey is done a long 40 traverses in N-S direction and another 40.0 Traverses along W-E directions. The preliminary results of the both surveys show some differences. These differences were removed by using first derivative filter. They both showed subsurface geometric shapes that are probably related to buried archeological walls. The mathematical modeling results showed walls of widths 0.3-0.4 meters at depths around 0.8 meters. These walls continue down to 2.3-2.5 meters in depth. The magnetic survey also showed many circular high magnetic anomalies within an area of 1.0 – 2.0 meters only. The mathematical modeling suggested that these anomalies could be corresponding to building poles made of andesite or basaltic rocks or they are buried metals objects.

Performance Improvement Using GOA-Based Fuzzy-2D-PIDF Controller for AGC of Multi-Area Power System

Automatic generation control (AGC) is an automation scheme that regulates the output of several generators employed at different areas of an interconnected power system simultaneously in response to load variation in the most economical way. This article implements a fuzzy-two degree of freedom-PID controller considering derivative filter (F-2D-PIDF) optimally tuned through grasshopper optimization algorithms (GOA) for AGC of a three unequal area interconnected power system. Initially, comparative performance analysis is carried out for conventional PID controllers optimally designed by particle swarm optimization, teaching learning-based optimization and GOA techniques. After ensuring better performance from GOA based PID controller, the study extended to establish dominance of the proposed F-2D-PIDF controller over others like PID, PID with derivative filter (PIDF), two degree of freedom-PIDF, and fuzzy-PIDF for the same power system in presence and absence of nonlinearities with GOA framework. In all these above studies, a load perturbation of 0.01 p.u. is applied in area-1. Comparative performance analysis reveals that GOA based F-2D-PIDF controller outperforms other controllers in all aspects. Finally, robustness of the proposed controller verified by varying system parameters and loading condition.

An intelligent medical decision support system for diagnosis of heart abnormalities in ECG signals

This work describes a novel method to detect a Bundle branch block and myocardial infarction from the multi-lead ECG signal. The clinical characteristics of BBB and MI extracted by using a derivative filter and continuous wavelet transform (CWT). The signal with the frequency below 50 Hz obtained and derivative-based filter applied to extract features. The continuous wavelet transforms also applied to the signals of BBB and MI. The CWT coefficients extracted, and the signals reconstructed from the wavelet to obtain the features. The feature vectors generated from each lead of both the methods computed using parameters such as spectral entropy, mean of peaks, total energy from power spectrum density, form factor, and root mean squared value. The results of both the derivative-based filter and CWT analyzed by applying these features to the classifiers. The accuracy of classification of diseases computed using SVM, KNN, Levenberg-Marquardt Neural Network (LMNN), and scaled conjugate gradient backpropagation network (SCG NN). The best accuracy obtained from the derivative filter and wavelet transform method is 96.4% using LMNN and SCGNN classifier and 96.4% using KNN and LMNN classifier respectively.

Geometric Derivative Filter for Image Enhancement

This article introduces and explains geometric derivative filter as a new method for image processing and enhancing quality of images.. It's mathematical concept will be explored and some examples of applying this filter to images will we illustrated.

Geometric Derivative Filter for Image Enhancement

This article introduces and explains geometric derivative filter as a new method for image processing and enhancing quality of images.. It's mathematical concept will be explored and some examples of applying this filter to images will we illustrated.