Dushyant Kumar Singh

Simulation of D-STATCOM for Voltage Fluctuation

This paper deals with control strategies for DSTATCOM (Distribution Static Compensator) for power quality improvement for a three-phase, three-wire distribution system. A three-leg voltage source inverter (VSI) configuration with a dc bus capacitor is employed as DSTATCOM. The PWM current controllers are designed analyzed and compare for PI controller. The capability of the DSTATCOM is demonstrated through results obtained using PSIM. The performance of the DSTATCOM acting as a shunt compensator is found satisfactory under varied load perturbations.

Gaussian elliptical fitting based skin color modeling for human detection

Human detection has now become an important and integral part of the maximum of computer vision applications. Surveillance is one such significant application. Surveillance with automatic human detection and event understanding is a faster and smart solution for todays surveillance. There have been a number of techniques which can be utilized for achieving human detection in an image or video. Each of these uses different types of features to exploit different characteristics of human being. So is the case that every of these techniques has some or other pitfall. Seeing all those, a novel technique based on skin color modeling is proposed in this paper for human detection in real-time surveillance videos. The proposed approach outperforms the other popular approaches by a significant rate on common measures of True Positive Rate, False Positive Rate and Accuracy.

Review of optical flow technique for moving object detection

Object detection in a video is a challenging task in the field of image processing. Some applications of the domain are Human Machine Interaction (HMI), Security and Surveillance, Supplemented Authenticity, Traffic Monitoring on Roads, Medicinal Imaging etc. There happens to be a number of methods available for object detection. Each of the method has some constraints on the kind of application it has been used for. This paper presents one of such method which is termed as Optical Flow technique. This technique is found to be more robust and efficient for moving object detection and the same has been shown by an experiment in the paper. Applying optical flow to an image gives flow vectors of the points corresponding to the moving objects. Next part of marking the required moving object of interest counts to the post processing. Post processing is the legitimate contribution of the paper for moving object detection problem. This here is discussed as Blob Analysis. It is tested on datasets available online, real time videos and also on videos recorded manually. The results show that the moving objects are successfully detected using optical flow technique and the required post processing.

Tracking Movements of Humans in a Real-Time Surveillance Scene

Increased security concern has brought up an acute need for being thoughtful in the area of surveillance. The normal trend of surveillance followed is a grid of CCTV cameras with control centralized at a room, which is manually looked upon by a caretaker. Many a times there is no regular watch carried by caretaker, instead logs of video footage are maintained, which are used in the case of any mishaps occurring. This is the practice followed even at major sensitive places. This is a retroactive kind of situation handling. A solution to this could be a system that continuously has a watch using a camera and indentifies a human object and then tracks its movement to identify any uncommon behavior. The sudden responsive action (reaction) made by the caretaker is the expected design objective of the system. In this paper we have proposed a system that analyzes the real-time video stream from camera, identifying a human object anfd then tracking its movement if it tries to go out of the field of view (FoV) of the camera. That is, the camera changes its FoV with the movement of the object.

Remotely controlled home automation system

This paper describes an investigation into the potential for remote controlled operation of home automation systems. It considers problems with their implementation, discusses possible solutions through various network technologies and indicates how to optimize the use of such systems. The home is an eternal, heterogeneous, distributed computing environment (Greaves, 2002) which certainly requires a careful study before developing any suitable Home Automation System (HAS) that will accomplish its requirements. Nevertheless the latest attempts at introducing Home Automation Systems [1] in actual homes for all kinds of users are starting to be successful thanks to the continuous standardization process that is lowering the prices and making devices more useful and easier to use for the end user. Even so several important issues are always to be handled strictly before developing and installing a Home Automation System; factors like security, reliability, usefulness, robustness and price are critical to determine if the final product will accomplish the expected requirements.

Case Studies on Intelligent Approaches for Static Malware Analysis

Malware poses a major threat to cyber security. It is a collective term to refer to a variety of forms of hostile software computer viruses, Internet worms, Trojan horses, ransomware, spyware, adware, scareware, and other malicious programs. They can disrupt computer operations, gain sensitive information, or gain access to private computer systems. Mostly signature-based antivirus tools that identify the malware by comparing the contents of the file to its database of known malware signatures are used nowadays as a defense against these malware. The number of malware samples to be analyzed by the security providers on a daily basis is continuously increasing. Therefore generic automated malware detection tools are needed to detect zero day threats. The behavioral patterns obtained can be used to detect and classify malware to known malware families using machine learning methods. As a result an unknown executable can be classified as benign or malicious depending on the result given by the learning algorithm. Here the paper details some intelligent techniques for malware analysis with all preprocessing steps required to analyze any PE sample.

Recognizing hand gestures for human computer interaction

As there are new developments and innovation in the field of computer technology, size of electronic devices is decreasing rapidly. Thus, there is a need of new input interface for such devices. Increasingly we are recognizing the importance of human computing interaction (HCI) and in particular vision-based gesture and object recognition. Simple interfaces already exist, such as embedded keyboard, folder-keyboard and mini-keyboard. However, these interfaces need some amount of space to use and cannot be used while moving. Touch screens are a good control interface nowadays and are globally used in many applications. By applying vision technology and controlling the devices by natural hand gestures, we can reduce the work space required. In this paper, we propose a novel approach that uses a video device to control the Laptop using gestures.