S. M. Kumbhare
Bio: S. M. Kumbhare is an academic researcher from Walchand College of Engineering, Sangli. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.
••05 Mar 2015
TL;DR: Vehicle detection is a process of analyzing the traffic and detecting the different types of vehicle on the road and Symmetrical SURF is one of the descriptor which is used for identifying the symmetrical points.
Abstract: During the last decades, there are various vehicle detection techniques are discovered and it is important for our society for managing and controlling on road traffic in the urban areas. Vehicle detection is a process of analyzing the traffic and detecting the different types of vehicle on the road. The vehicle is a symmetrical object from front and back. For the detection of vehicle, Symmetrical SURF (Speeded-Up Robust Feature) is one of the descriptor which is used for identifying the symmetrical points and these points is the mirror version of each other, all the possible matching pairs are identified. After that, detecting the central line and ROI of each frame of the vehicle is done.
17 May 2023
TL;DR: In this paper , it has been established after careful examination that the majority of accidents and in fatalities as a result of inadequate communication with the appropriate medical authorities and the following lack of urgent medical care.
Abstract: The average number of vehicles on the road worldwide has increased as cars and other vehicles become more and more accessible. Our lives are now easier because of the technology and infrastructure that are developing quickly. The advent of technology has also enhanced the risks associated with traffic and Regular traffic accidents result in a number of accidents on this dynamic planet and significant loss of life and property due to inadequate emergency facilities. Accident victims suffer greatly and lose significant time and money as a result. It has been established after careful examination that the majority of accidents and in fatalities as a result of inadequate communication with the appropriate medical authorities and the following lack of urgent medical care. There are many deaths as a result of inadequate crisis management. As a result, this research study intends to provide crisis administrations to the person who meets with an accident as soon as time permits
TL;DR: In this article, the authors introduce commonly used sensors for vehicle detection, lists their application scenarios and compares the strengths and weaknesses of different sensors, and several simulation platforms related to UGVs are presented for facilitating simulation testing of vehicle detection algorithms.
Abstract: Unmanned ground vehicles (UGVs) have great potential in the application of both civilian and military fields, and have become the focus of research in many countries. Environmental perception technology is the foundation of UGVs, which is of great significance to achieve a safer and more efficient performance. This article firstly introduces commonly used sensors for vehicle detection, lists their application scenarios and compares the strengths and weakness of different sensors. Secondly, related works about one of the most important aspects of environmental perception technology-vehicle detection-are reviewed and compared in detail in terms of different sensors. Thirdly, several simulation platforms related to UGVs are presented for facilitating simulation testing of vehicle detection algorithms. In addition, some datasets about UGVs are summarized to achieve the verification of vehicle detection algorithms in practical application. Finally, promising research topics in the future study of vehicle detection technology for UGVs are discussed in detail.
TL;DR: A distributed parking prototype is developed to mitigate the problems faced by a common man and in the process conserving fuel and helping reduce global warming, pollution as well.
Abstract: Vehicle parking in today's date has turned into a noteworthy issue in urban territories, because of the absence of parking facilities and poor management. Problems emerging from the absence of parking facilities and poor administration incorporate movement clog, expanded contamination, expanded utilization of fuel.To relieve these issues, a model has been produced with the android application, appropriated frameworks, image processing. The prototype with the help of an android application gives the information regarding the availability of car parking to the user directly. Delivering User the information regarding the parking space availability will thus reduce the time, fuel and efforts invested in search of a parking space. This will also lead to a reduction in traffic congestion, ultimately leading to less pollution. A database maintained for the availability of parking space can be used for better management of parking spaces. For detection of car parking spaces, image processing is helpful which will determine the parking availability. This prototype hence, will reduce manpower needs and increase the flexibility and security. The image processing at the local server level and only providing the required information to the central server thus optimizes the process followed by this prototype. Thus, a distributed parking prototype is developed to mitigate the problems faced by a common man and in the process conserving fuel and helping reduce global warming, pollution as well.
TL;DR: The car recognition is part of the field of traffic surveillance on the image using the form-based feature as a unique feature and the use of FFT and MLC in the car object recognition has never been used.
Abstract: The car recognition is part of the field of traffic surveillance on the image. In general, the car recognition using the form-based feature as a unique feature. Another feature in object recognition is the frequency feature. One feature of frequency is the Fourier feature, this feature is obtained by using Fast Fourier Transform (FFT) method. The object recognition can be done by determining the maximum value of likelihood and classifying it with Maximum Likelihood Classification (MLC). The use of FFT and MLC in the car object recognition has never been used. The results of both are in a good accuracy that is 76%.