Kamarul Hawari

Abstract Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical ...

According to the U.S. National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year[1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, Probabilistic Hough Transform (PHT) is presented in this paper for intelligent Lane markers recognition which use a fixed camera installed on the vehicle to transmit video information. The result of experiment proved that under inconsistent illumination and a diversity of road conditions, the accuracy and efficiency of developed system have been improved greatly.

According to the U.S. National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year[1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, Probabilistic Hough Transform (PHT) is presented in this paper for intelligent Lane markers recognition which use a fixed camera installed on the vehicle to transmit video information. The result of experiment proved that under inconsistent illumination and a diversity of road conditions, the accuracy and efficiency of developed system have been improved greatly.

It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection framework that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space and HSV color space. Firstly, we build a skin Gaussian model in Cg-Cr color space, and then some constraints are used to get candidates of face. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions..

In this study, an approach of extraction analysis for bearing fault diagnosis of rotating machinery based on thermogram investigation using color features is proposed in this paper. This research was proposed since condition monitoring and motor failures are great concern in industries. Early fault detection in machineries can avoid production lost and reducing maintenance costs. Therefore, in this work, infrared thermography (IRT) is used as a tool to detect early sign for bearing fault since this infrared thermography (IRT) is one of the most effective non-destructive testing techniques of condition monitoring and fault diagnostics. By using this infrared thermography (IRT) technology, the information of machine condition can be analyzed. In the present study, 300 thermal images are used in this simulation process whereby the images are classified into two classes namely normal and abnormal. The first class consists of 150 images normal bearing while another 150 images denote abnormal bearing class. SURF feature-based algorithm, RGB color space and active contour segmentation are employed in this paper in order to process and differentiate between normal and abnormal bearing image by means of color features called statistical technique. The experiment results indicate that this statistical features of RGB color space able to distinguish the differences between normal and abnormal features of bearing in machinery system.

Inspired by the estimation capability of Kalman filter, we have recently introduced a novel population-based optimization algorithm called simulated Kalman filter (SKF). Every agent in SKF is regarded as a Kalman filter. Based on the mechanism of Kalman filtering, which includes prediction, measurement, and estimation, the global minimum/maximum can be estimated. Measurement process, which is required in Kalman filtering, is mathematically modelled and simulated. Agents communicate among them to update and improve the solution during the search process. Inspired by the bird flocking, particle swarm optimization (PSO) has been introduced in 1994. In PSO, a swarm of agent search the global minimum/maximum by velocity and position updates, which are influenced by current position of agent, current position of agent, personal best, and global best of the swarm. In this research, SKF and PSO are hybridized in such a way that PSO is employed as prediction operator in SKF. The performance of the proposed hybrid SKF-PSO algorithm (SKF-PSO) is compared against SKF and PSO using CEC2014 benchmark dataset for continuous numerical optimization problems. Based on the analysis of experimental results, we found that the proposed hybrid SKF-PSO is superior to both SKF and PSO algorithm.

— Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.

Global positioning system (GPS) is being actively employed in a variety of vehicular monitoring systems such as automated car navigation, emergency assistance, fleet management and automotive assistance. Nowadays easily observed many passengers footed at the Bus stations waiting for their desired bus. This paper considers performance issues in Public transport monitoring system that utilize GPS and embedded RF radio chip. For the purpose, a new intelligent Multi ID buses movement monitoring and station reporting system comprising of GPS, in collaboration with succession of sophisticated Transceivers modules, is presented here. In addition to some fundamental functions such as real-time monitoring, some featured functions are combined to make the system compatible with the daily operations of any public transport scheme. Because of performance and cost constraints, this monitoring system is carefully designed to balance system partitioning and resource sharing. The proposed method will surely provide smooth and linear transmission of location information to the bus stations which led people to take decision either to wait for Bus or not.

The paper presents switching techniques for pulse-width-modulated-based z-source inverter; simple boost PWM, maximum boost PWM, maximum constant boost PWM, modified-reference PWM, modified space vector PWM, hysteresis current control, and sine carrier PWM. Concepts and ideas behind the techniques are briefly explained. An overall view is summed up of the PWM controls, in terms of their achievements and system involvement in ZSI.

Ordinary CCTV can only be used to record incidents if it occur. It works without preventing it and it is only useful to be an evidence for the investigation. The purpose of developing this project is as the earlier prevention to avoid crime by giving alert or feedback from the object that was detected from captured video. The captured video in this project will be convert into frame of images and being analyze by using MATLAB software that already consist all the techniques of image processing. The output of this project will be classified if there is any motion or not by using the value of total sum of pixel value from each image data. The classification is actually based on the threshold value. This project indirectly reduce weakness and careless of human guard observation as it give continuous 24-hour monitoring of surveillance video to alert security officers to an intruder potential.

Abstract In machine vision application, the main part to analyze an image is to identify its features which contribute to efficiency of the system. Many applications in vision system and image analysis used face detection as a feature of their whole system development. In application such as video surveillance, fatigue detection and security system, face is a fundamental step in the analysis before proceed to system implementation. It is very challenging to recognize a face from an image due to the wide variety of face and the ...

Embedded systems have an everyday presence and direct impact in every day's lives. Therefore, learning institutions are continuously improving their courses in microcontroller and embedded system programming. Although the diversity of curriculums, the availability of learning tools, where the student can practice and improve their skills, is a key factor to the success of the learning process. The platform developed and presented in this paper results from author's experience in teaching embedded systems. From the analysis of teaching/learning needs, a learning environment based on the Freescale HC11, MCS51, and Microchip PIC 16 Series families was designed. This tool can be expanded by modules and adjusted, at a specific time, to student's real needs. All modules can be interconnected by an IDE bus, allowing expanding the capabilities of the platform. The developed modules allow the practice of subjects related with digital IO, analogue interface, user interface, wireless communications, and energy management and conservation.

A weed can be thought of as any plant growing in the wrong place at the wrong time and doing more harm than good. Weeds compete with the crop for water, light, nutrients and space, and therefore reduce crop yields and also affect the efficient use of machinery. The most widely used method for weed control is to use agricultural chemicals (herbicides and fertilizer products). This heavy reliance on chemicals raises many environmental and economic concerns, causing many farmers to seek alternatives for weed control in order to reduce chemical use in farming. Since hand labor is costly, an automated weed control system may be economically feasible. A real-time precision automated weed control system could also reduce or eliminate the need for chemicals. In this research, an intelligent real-time automatic weed control system using image processing has been developed to identify and discriminate the weed types namely as narrow and broad. The core component of vision technology is the image processing to recognize type of weeds. Two techniques of image processing, GLCM and FFT have been used and compared to find the best solution of weed recognition for classification. The developed machine vision system consists of a mechanical structure which includes a sprayer, a Logitech web-digital camera, 12v motor coupled with a pump system and a small size CPU as a processor. Offline images and recorded video has been tested to the system and classification result of weed shows the successful rate is above 80%.

Abstract According to the US National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year [1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, ...