License plate recognition ieee paper,esther hicks net worth tx,address search engine in india - 2016 Feature

13.12.2015
Observe up to 16 live cameras onscreen, recall recorded events at pumps, register, or shop lifters by Date & Time. AbstractAbstract of Indian License Plate Character Recognition System using Neural Network ieee matlab project.Intelligent Transportation System (ITS) has become an integral part of the Transportation Industry these days and it consists of License Plate Recognition (LPR) System. After the segmentation of elements (characters and numbers), the final module in the license plate recognition process is character recognition. This step is the main part of the system and is called as Character Recognition step, where segmented characters are recognized.
Transcript1)License Plate Character Recognition System using Neural NetworkInternational Journal of Computer Applications (0975 a€“ 8887) Volume 25a€“ No.10, July 2011 36 License Plate Character Recognition System using Neural Network Anuja P.
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License Plate Recognition is also called Car Plate Recognition (CPR) or Automatic Number Plate Recognition (ANPR) System.
Although there are many techniques present and applied for character recognition like statistical, syntactic and neural networks in this research, character recognition is performed by using feature extraction. In LPR System, when a vehicle steps over magnetic loop detector it senses car and takes image of the car, following image preprocessing operations for improvement in the quality of car image.
First original car image is taken as input; image preprocessing is done on this image and in the last step plate is extracted from preprocessed image. Traditional methods used for number plate recognition were OCR "Optical Character Recognition" and "Formula Based Recognition".


They are Close Operation To Remove The Gaps, Between Characters Repeated Image Opening Operation For Removal Of Unnecessary Components, Subtraction Of The Image Obtained From The Gray Image. As Neural Network" is an intelligence engine, it ensures greater accuracy rate along with better recognition speed. ABSTRACT Intelligent Transportation System (ITS) has become an integral part of the Transportation Industry these days and it consists of License Plate Recognition (LPR) System. Fan-beam Transform is used for computing an alternative mathematical representation of an image using Fan-beam projections. License Plate Recognition is also called Car Plate Recognition (CPR) or 31)Automatic Number Plate Recognition (ANPR) System.
A Feature Extraction Technique Based on Character Geometry for Character Recognition" describes a geometry based technique for feature extraction. In the first step image enhancement is performed using Contrast stretching followed by Tophat-Bothat Transform.
After edge detection series of morphological operations are performed in order to detect the license plate. Then character segmentation is done using line scanning technique, scanning is done from left 91)to right of the plate. After Character Segmentation, feature extraction is performed to obtain the unique features of every character. FEATURE EXTRACTION In this paper, as Neural Network is used for character recognition, Feature Extraction is an important step for training and simulating the Neural Network. CONCLUSION In this paper, method for character recognition of license plate image based on two Neural Network techniques and two feature extraction approaches are proposed.


It is observed that, as fan beam feature extraction method has more features for training the neural network thus its simulation accuracy is higher. Using Fan-beam for feature extraction Back Propagation and Learning Vector Quantization Neural Networks are trained. Also more number of fonts can be used for training the network for improving the accuracy of the character recognition. ACKNOWLEDGMENTS I wish to express my sincere thanks and deep sense of gratitude to respected mentor and guide Ms. Shalini Bhatia, Assistant Professor in Computer Engineering Department of Thadomal Shahani Engineering College., for the technical advice, encouragement and constructive criticism, which motivated to strive harder for excellence. 451)[7] Dinesh Dileep, a€?A Feature Extraction Technique Based On Character Geometry For Character Recognitiona€?, In proc. Shipman, a€?OCR (Optical Character Recognition): Converting paper documents to texta€? In proc. International Journal of Computer Applications (0975 a€“ 8887) Volume 25a€“ No.10, July 2011 39 [10] cctvx a€“ cctv [Online].




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