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Monisha, R.
- Automated Map Generating and Ranging Robot
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Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Tamilnadu College of Engineering, Karumathampatti, Coimbatore-641659, Tamilnadu, IN
1 Department of Electrical and Electronics Engineering, Tamilnadu College of Engineering, Karumathampatti, Coimbatore-641659, Tamilnadu, IN
Source
Digital Image Processing, Vol 11, No 3 (2019), Pagination: 51-53Abstract
Robotic mapping and exploration is an important contribution in the area of SLAM for autonomous robots. The autonomous mapping learning problem is focused in the content. Solutions includes uncertainty - driven exploration, active loop closing and coordination of multiple robots, learning and incorporation background knowledge and dealing with dynamic environments. One requirement of SLAM is a range measurement device, of the method for observing the environment around the robot. Laser sensor such as LIDAR is the most common measuring device. Laser sensor are easy to use and very precise however, they are also extremely expensive.
Thus sonar can be used and the device is especially useful for mapping underwater environment. This optical reader can came in 2D or even 3D formats. Plotting the data of US sensor which is rotating a 360 degree, will yield a map of one plane. By The height of the setup consequent plane's map can be obtained.
References
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- Automatic Parking System using Vehicle License Plate Detection
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Authors
Affiliations
1 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
2 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
1 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
2 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
Source
Digital Image Processing, Vol 13, No 2 (2021), Pagination: 33-40Abstract
With phenomenal increase in the number of vehicles, vehicular systems and parking systems are a major challenge faced by urban cities. Parking systems currently rely on manual labour for noting down the registration numbers of vehicles entering the parking system. Our project aims at developing a parking system what would detect a vehicle while entering in the parking lot, and also would automatically recognize its registration number at day and night time. Parking lots are generally closed structures so there is always low light and at night time there are extremely low light conditions. Any camera would fail to provide noise free image at this condition. So there is need for low light enhancement. This paper discusses some of the existing low image enhancement algorithms. From the enhanced image, computation is done in detecting the vehicle, classifying it into4 wheelers or 2 wheeler vehicles and also extracting the registration number from the detected license plate. This paper deals with several existing architectures and models which perform ALPR on benchmark dataset.Keywords
ALPR, Low Light Enhancement, License Plate Detection, Character Recognition.References
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