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Narote, S. P.
- Vehicle Number Plate Detection and Character Segmentation
Authors
1 Department of Electronics Engineering, Vishwakarma Institute of Technology, Pune, IN
2 Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune, IN
Source
Digital Image Processing, Vol 3, No 4 (2011), Pagination: 250-253Abstract
In this paper, we present Automatic Number Plate detection and character segmentation for Indian Cars. Number plate design protocols are not followed in India. Characters on plate are in different Indian languages, as well as in English. We present the number plate detection and character segmentation work, with English characters. Number plate detection is quite challenging task, mainly due to diversity of plate formats, and the non-uniform illumination conditions during the image acquisition. To eliminate possible fake candidate, extracted plate regions is evaluated on the basis of geometric features of the plate: density, aspect ratio and horizontal cuts. Character segmentation is done by using connected component and vertical projection analysis. The performances on an average are: Number Plate Detection rate: 85%, Character Segmentation rate: 83%.Keywords
Vehicle Number Plate, Number Plate Detection, Character Segmentation.- Human Identification by Gait Recognition
Authors
1 Sinhgad College of Engineering, Pune from Pune University, IN
2 Sinhgad College of Engineering, Pune, IN
Source
Biometrics and Bioinformatics, Vol 4, No 1 (2012), Pagination: 1-3Abstract
As a biometric, gait has several attractive properties.Acquisition of images of an individual’s gait can be done easily inpublic areas, with simple instrumentation, and does not require thecooperation or even awareness of the individual under observation.Recognition of gait through gait analysis is an important researchtopic, with potential application in video surveillances, tracking,access control, smart interfaces and monitoring. Gait recognition is theprocess of identifying an individual by the manner in which they walk.The aim of this paper is the to compare the two algorithms of gaitrecognition system. There are so many methods like dynamic timewarping, gait energy image, hidden markov method, etc. is explainedby authors. In this paper we proposed an automatic gait recognitionapproach based on the features like variance and edge of videosequences. The gait signature vectors are constructed to identifydifferent subjects. Finally, similarity measurement based on the k NNclassifier is carried out to recognize the different subjects in whichthey walk. Finally, feature outputs for variance and edge detection arecompared. The results obtained by variance method and edge detectionmethod are 94% and 68.8% resp. From graphical output we concludedthat the results obtained by variance methods give the better outputthan canny edge detection method.