Segmenting characters from license plate images with little prior knowledge

In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme. © 2010 IEEE

Segmentation of characters on car license plates

License plate recognition usually contains three steps, namely license plate detection/localization, character segmentation and character recognition. When reading characters on a license plate one by one after license plate detection step, it is crucial to accurately segment the characters. The segmentation step may be affected by many factors such as license plate boundaries (frames). The recognition accuracy will be significantly reduced if the characters are not properly segmented. This paper presents an efficient algorithm for character segmentation on a license plate. The algorithm follows the step that detects the license plates using an AdaBoost algorithm. It is based on an efficient and accurate skew and slant correction of license plates, and works together with boundary (frame) removal of license plates. The algorithm is efficient and can be applied in real-time applications. The experiments are performed to show the accuracy of segmentation. © 2008 IEEE

Number Plate Recognition

With India growing it has made the ownership of vehicles a necessity. This has resulted in an civic problem. Parking areas have become congested due to the growing numbers of vehicles. The Number Plate Recognition System (NPR) plays an important role in different application as it is from parking to monitoring urban traffic and tracking automobile thefts. There are various NPR systems available today which work with different methodologies. In this paper, we attempt to review the various techniques and their usage. The NPR system has been implemented using template Matching and its accuracy was found to be 90.2% for number plate

Road Vehicle Monitoring System Based on Intelligent Visual Internet of Things

In recent years, with the rapid development of video surveillance infrastructure, more and more intelligent surveillance systems have employed computer vision and pattern recognition techniques. In this paper, we present a novel intelligent surveillance system used for the management of road vehicles based on Intelligent Visual Internet of Things (IVIoT). The system has the ability to extract the vehicle visual tags on the urban roads; in other words, it can label any vehicle by means of computer vision and therefore can easily recognize vehicles with visual tags. The nodes designed in the system can be installed not only on the urban roads for providing basic information but also on the mobile sensing vehicles for providing mobility support and improving sensing coverage. Visual tags mentioned in this paper consist of license plate number, vehicle color, and vehicle type and have several additional properties, such as passing spot and passing moment. Moreover, we present a fast and efficient image haze removal method to deal with haze weather condition. The experiment results show that the designed road vehicle monitoring system achieves an average real-time tracking accuracy of 85.80% under different conditions

Off-line Arabic Handwriting Recognition System Using Fast Wavelet Transform

In this research, off-line handwriting recognition system for Arabic alphabet is introduced. The system contains three main stages: preprocessing, segmentation and recognition stage. In the preprocessing stage, Radon transform was used in the design of algorithms for page, line and word skew correction as well as for word slant correction. In the segmentation stage, Hough transform approach was used for line extraction. For line to words and word to characters segmentation, a statistical method using mathematic representation of the lines and words binary image was used. Unlike most of current handwriting recognition system, our system simulates the human mechanism for image recognition, where images are encoded and saved in memory as groups according to their similarity to each other. Characters are decomposed into a coefficient vectors, using fast wavelet transform, then, vectors, that represent a character in different possible shapes, are saved as groups with one representative for each group. The recognition is achieved by comparing a vector of the character to be recognized with group representatives. Experiments showed that the proposed system is able to achieve the recognition task with 90.26% of accuracy. The system needs only 3.41 seconds a most to recognize a single character in a text of 15 lines where each line has 10 words on average

NASA Tech Briefs, October 2009

Topics covered include: Light-Driven Polymeric Bimorph Actuators; Guaranteeing Failsafe Operation of Extended-Scene Shack-Hartmann Wavefront Sensor Algorithm; Cloud Water Content Sensor for Sounding Balloons and Small UAVs; Pixelized Device Control Actuators for Large Adaptive Optics; T-Slide Linear Actuators; G4FET Implementations of Some Logic Circuits; Electrically Variable or Programmable Nonvolatile Capacitors; System for Automated Calibration of Vector Modulators; Complementary Paired G4FETs as Voltage-Controlled NDR Device; Three MMIC Amplifiers for the 120-to-200 GHz Frequency Band; Low-Noise MMIC Amplifiers for 120 to 180 GHz; Using Ozone To Clean and Passivate Oxygen-Handling Hardware; Metal Standards for Waveguide Characterization of Materials; Two-Piece Screens for Decontaminating Granular Material; Mercuric Iodide Anticoincidence Shield for Gamma-Ray Spectrometer; Improved Method of Design for Folding Inflatable Shells; Ultra-Large Solar Sail; Cooperative Three-Robot System for Traversing Steep Slopes; Assemblies of Conformal Tanks; Microfluidic Pumps Containing Teflon[Trademark] AF Diaphragms; Transparent Conveyor of Dielectric Liquids or Particles; Multi-Cone Model for Estimating GPS Ionospheric Delays; High-Sensitivity GaN Microchemical Sensors; On the Divergence of the Velocity Vector in Real-Gas Flow; Progress Toward a Compact, Highly Stable Ion Clock; Instruments for Imaging from Far to Near; Reflectors Made from Membranes Stretched Between Beams; Integrated Risk and Knowledge Management Program -- IRKM-P; LDPC Codes with Minimum Distance Proportional to Block Size; Constructing LDPC Codes from Loop-Free Encoding Modules; MMICs with Radial Probe Transitions to Waveguides; Tests of Low-Noise MMIC Amplifier Module at 290 to 340 GHz; and Extending Newtonian Dynamics to Include Stochastic Processes

Vehicle surface contamination, unsteady flow and aerodynamic drag

The rear surfaces of blunt-ended vehicles, such as SUVs, are vulnerable to the build-up of contaminants thrown up from wet road surfaces by their tyres. This can compromise drivers’ vision, vehicle visibility, sensor performance and aesthetics. Vision will be reduced if the rear screen and lenses of camera systems become obscured. Similarly, sensing methods such as Light Detection and Ranging [LIDAR], introduced to support higher-level Advanced Driver Assistance Systems [ADAS] and autonomous driving are also vulnerable to contaminant accumulation. In addition, vehicle users may find that dirt is transferred to their hands and clothes as they access the rear load space. Finally, rapid soiling of external surfaces can be perceived as degrading the aesthetics of premium vehicles. Such deposition is a manifestation of unsteady aerodynamics – particularly the interaction between tyre spray, wheel wakes and the vehicle rear wake. These wake structures also strongly influence aerodynamic drag which, in turn affects CO2 emissions for Internal Combustion Engine [ICE] powered cars and the range of Battery Electric Vehicles [BEV]. Hence, automotive manufacturers need a simulation approach that can be used to minimise these characteristics concurrently during vehicle development. This work met that need by developing and deploying an innovative simulation process which predicts both contaminant accumulation and drag at the same time, by numerically representing unsteady aerodynamics, tyre spray and surface water behaviour. It is now integrated into the vehicle development process at Jaguar Land Rover [J/LR] where it is being used to develop new cars. This has been achieved by using a series of novel simplified vehicle geometry and spray systems to incrementally develop and validate the simulation strategy. The work culminated with its application to a production vehicle and subsequent validation against full scale experiments, providing the first quantification of accuracy for simulations of rear surface contamination. This novel simulation approach is combined with original experiments to show that reduced vehicle ride heights can lead to increased rear surface contamination, by reducing underbody flow and moving the vehicle wake closer to the highly contaminated wheel wakes. This provides a challenge for vehicle developers as lower ride heights are used to reduce aerodynamic drag; an increasingly important objective for both ICE and BEV product development, to support lower CO2 emissions and enhanced range, respectively. Finally, the first evidence is presented to suggest that aerodynamically improved underfloors can increase rear surface contamination, or at least redistribute it towards the lower regions of the vehicle rear, such as the bumper. This raises a risk for future BEVs which combine aerodynamically advantageous smooth underfloors with vulnerable ADAS features, such as rear bumper mounted LIDAR

NASA patent abstracts bibliography: A continuing bibliography. Section 1: Abstracts (supplement 29)

Abstracts are provided for 115 patents and patent applications entered into the NASA scientific and technical information system during the period January 1986 through June 1986. Each entry consists of a citation, an abstract, and in most cases, a key illustration selected from the patent application