Yasir Mohd Mustafah

Bio: Yasir Mohd Mustafah is an academic researcher from International Islamic University Malaysia. The author has contributed to research in topics: Object detection & Smart camera. The author has an hindex of 11, co-authored 56 publications receiving 390 citations. Previous affiliations of Yasir Mohd Mustafah include University of Queensland & NICTA.

Stereo vision images processing for real-time object distance and size measurements

Abstract: Human has the ability to roughly estimate the distance and size of an object because of the stereo vision of human's eyes. In this project, we proposed to utilize stereo vision system to accurately measure the distance and size (height and width) of object in view. Object size identification is very useful in building systems or applications especially in autonomous system navigation. Many recent works have started to use multiple vision sensors or cameras for different type of application such as 3D image constructions, occlusion detection and etc. Multiple cameras system has becoming more popular since cameras are now very cheap and easy to deploy and utilize. The proposed measurement system consists of object detection on the stereo images and blob extraction and distance and size calculation and object identification. The system also employs a fast algorithm so that the measurement can be done in real-time. The object measurement using stereo camera is better than object detection using a single camera that was proposed in many previous research works. It is much easier to calibrate and can produce a more accurate results.

Indoor UAV Positioning Using Stereo Vision Sensor

Abstract: The UAV system has becoming increasingly popular in the application such as surveillance, reconnaissance, mapping and many more. Different from guided vehicles, which rely on the pilot to navigate the system, UAV relies on autonomous control to provide this functionality. Hence, precise feedback on the position of the UAV is very important. Unlike outdoor positioning, there are no standard, low cost indoor positioning systems available. Hence, we proposed to utilize a stereo vision sensor as an indoor positioning system for our UAVs. The system utilizes two video cameras for stereo vision capture and set of fast algorithms so that position information can be obtained in real-time. Experiment conducted shows that the system could provide a reliable accuracy in real-time.

Performance Comparison between RGB and HSV Color Segmentations for Road Signs Detection

Abstract: This paper compares the performance of RGB and HSV color segmentations method in road signs detection. The road signs images are taken under various illumination changes, partial occlusion and rotational changes. The proposed algorithms using both RGB and HSV color space are able to detect the 3 standard types of colored images namely Red, Yellow and Blue. The experiment shows that the HSV color algorithm achieved better detection accuracy compared to RGB color space.

An Automated Face Recognition System for Intelligence Surveillance: Smart Camera Recognizing Faces in the Crowd

Abstract: Smart cameras are rapidly finding their way into intelligent surveillance systems. Recognizing faces in the crowd in real-time is one of the key features that will significantly enhance intelligent surveillance systems. The main challenge is the fact that the high volumes of data generated by high-resolution sensors make it computationally impossible for mainstream computers to process. In our proposed technique, the smart camera extracts all the faces from the full-resolution frame and sends the pixel information from these face areas to the main processing unit as a auxiliary video stream - potentially achieving massive data rate reduction. Face recognition software running on the main processing unit then performs the required pattern recognition.

Development of Autonomous Radiation Mapping Robot

Abstract: This paper discusses the development of a spatial radiation map by an autonomous mobile robot that is equipped with Geiger Muller sensor. Mapping of gamma radiation autonomously using robot as agents will help to prevent harm to human especially when radiation related disaster occur. Hence, we intend to develop a gamma radiation mapping system that reads and process location data of a mobile robot with encoder as well as the radiation data transmitted by the Geiger Muller sensor on the mobile robot. A grid based algorithm was develop to build the radiation map. The system was then tested under several conditions. The results of the spatial distribution map with respect to respective waypoints were discussed at the end of this paper.

The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges

Abstract: The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in the UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate more than $45 Billion market value of UAV usage. In this paper, we present UAV civil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

A Comparative Study on Human Activity Recognition Using Inertial Sensors in a Smartphone

Abstract: Activity recognition plays an essential role in bridging the gap between the low-level sensor data and the high-level applications in ambient-assisted living systems. With the aim to obtain satisfactory recognition rate and adapt to various application scenarios, a variety of sensors have been exploited, among which, smartphone-embedded inertial sensors are widely applied due to its convenience, low cost, and intrusiveness. In this paper, we explore the power of triaxial accelerometer and gyroscope built-in a smartphone in recognizing human physical activities in situations, where they are used simultaneously or separately. A novel feature selection approach is then proposed in order to select a subset of discriminant features, construct an online activity recognizer with better generalization ability, and reduce the smartphone power consumption. Experimental results on a publicly available data set show that the fusion of both accelerometer and gyroscope data contributes to obtain better recognition performance than that of using single source data, and that the proposed feature selector outperforms three other comparative approaches in terms of four performance measures. In addition, great improvement in time performance can be achieved with an effective feature selector, indicating the way of power saving and its applicability to real-world activity recognition.

Handbook of Medical Imaging—Processing and Analysis

Abstract: In summary, this large, edited volume would provide a valuable addition to the shelf of anyone interested in the rapidly-developing field of medical image processing. At £79.95 it appears expensive, but given the coverage of the field, the page count and the quality of the illustrations, it would appear to be well worth the outlay.