1 Object Recognition Basics and Visual Surveillance (original) (raw)
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Object Recognition Basics and Visual Surveillance
2008
In this report basic principles of object recognition techniques are described and also some of the visual surveillance applications are given as examples of different techniques. In our study, suitable recognition techniques will be used for the traffic characterization of recognized images for wireless multimedia sensor networks.
Image Recognition Traffic Patterns for Wireless Multimedia Sensor Networks
2008
The objective of this work is to identify some of the traffic characteristics of Wireless Multimedia Sensor Networks (WMSN). Applications such as video surveillance sensor networks make use of new paradigms related with computer vision and image processing techniques. These sensors do not send whole video sequences to the wireless sensor network, but objects of interest detected by the camera. In order to able to design appropriate networking protocols, a better understanding of the traffic characteristics of these multimedia sensors is needed. In this work, we analyze the traffic differences between cameras that send whole coded images and those that first process and recognize objects of interest using Object Recognition techniques.
Traffic Analysis Based On Image Processing
2015
Traffic information is an important tool in the planning, maintenance and control of any modern transport system. The Image Processing algorithm has been applied to measure basic traffic parameters such as traffic volume, timer to green signal for each path to reduce traffic at the junction side. In this paper we apply edge-detection techniques to the key regions or windows. Also, background subtraction algorithm is a very important part of Intelligent Traffic System (ITS) applications for successful segmentation of objects from video sequence to control the Traffic at heavy traffic junction. Automatic Number plate Recognition (ANPR) is an application of Traffic Analysis which use mainly for security purpose which identifies the character directly from the image of license plate.
Video Image Processing For Traffic Analysis
Jurnal Teknologi, 1992
In recent years the application of computer-based image processing techniques to a range of traffic data collection tasks has been successfully demonstrated. In a similar field of research carried out by the author at the University of Wales College of Cardiff, a system based on commercial image processing hardware, a 80486 IBM PC-AT and a video recorder was assembled. The main aim was to develop a system for automatic vehicle data measurement and to extend its application to the collection and analysis of pedestrian data. This paper will focus on the development of the system for vehicle detection and measurement. A direct segmentation technique on the video images was adopted as a standard method of vehicle identification. The identification of the presence of an individual vehicle based on brightness information at relatively few sample points within the images was possible. Double threshold values were applied to the area of interest for the conversion of the area into a binary ...
Journal of Electrical, Electronic, Information, and Communication Technology
The number of positive Covid-19 cases in Indonesia continue to increase. This increase influenced by the behavior of Indonesian citizens in dealing with the pandemic, one of which is rarely wearing masks. In this study, we implemented an object detection method for intelligent surveillance systems (ISS) at the Faculty of Engineering, Universitas Sebelas Maret (UNS), Surakarta. By implementing face detection and mask detection, the surveillance system can recognize whether a person in a CCTV video frame is wearing a mask or not. In addition, deep metric learning and histogram of gradient (HOG) are applied to recognize faces of unmasked people in images. The test results show that the surveillance system can recognize the use of masks with 75%-87% accuracy rate. Furthermore, the accuracy rate for facial recognition on images ranges from 69% -100% for each person
Automatic Object Detection in Image Processing: A Survey
Digital image processing is a fast growing field and many applications are developed in science and engineering. Image processing has the possibility of establish the latest machine that could perform the visual functions of all living beings. Object recognition is one of the most imperative features of image processing. Object detection from a satellite image or aerial image is a type of the object recognition system. This system is the most interesting and challenging research topic from past few years. It is known that the traffic is increasing day by day in the developing and developed countries. Satellites images are normally used for weather forecasting and geographical applications. So, Satellites images may be also good for the traffic detection system using Image processing.
Object Detection and Identification in Surveillance Images using Image Processing
International Journal of Engineering and Advanced Technology, 2019
The goal of object detection and identification in surveillance images using image processing is to detect a particular part of the image from surveillance camera like an object’s position, movement, and its sequence. Object tracking and recognition deal with recognizing the image of video which can differ in color, range, size, illumination changes with time and some cluttered images. As this paper has been surveying and an algorithm has been proposed and implemented, the identified object has freed from the shadow, clutter, illumination changes were detected and eliminated appropriately.
Image analysis architectures and techniques for intelligent surveillance systems
Iee Proceedings-vision Image and Signal Processing, 2005
Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed, generic and robust. Our second goal is to have a development platform that allows researchers to conceive and easily test new vision algorithms thanks to its modularity and easy set-up.
Video cameras are becoming a ubiquitous feature of modern life, useful for surveillance, crime prevention, and forensic evidence. We cannot solely rely upon human efforts to watch and shift through hundreds and thousands of video frames for crime alerts and forensic analysis. That is a non-scalable task. We need a semi-automated video analysis and event recognition system that can provide timely warnings to alert security personnel, and that can substantially reduce the search space for forensic analysis tasks. This survey describes the approach of wireless intelligent video surveillance system using moving object recognition technique.
Object recognition is concerned with determining the identity of an object being observed in the image from a set of known labels. Oftentimes, it is assumed that the object being observed has been detected or there is a single object in the image. Object Recognition is the critical task in many computer vision applications such as video surveillance, vehicle parking system, person identification, and behavior analysis. Object Recognition area especially for human and vehicle is currently most active research topic. Typically it includes the phases like pre-processing, Background extraction, object detection, recognition and classification. In this paper, we review current methods for the object recognition.