Soomro et al., 2012 - Google Patents
Vehicle number recognition system for automatic toll tax collectionSoomro et al., 2012
View PDF- Document ID
- 11842482863984629189
- Author
- Soomro S
- Javed M
- Memon F
- Publication year
- Publication venue
- 2012 international conference of robotics and artificial intelligence
External Links
Snippet
Vehicle Number Recognition (VNR) is an image processing technology which uses efficient algorithms to detect the vehicle number from real time images. The objective is to design an efficient Vehicle Number Recognition System & to implement it for automatic toll tax …
- 238000005516 engineering process 0 abstract description 6
Classifications
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
- G06K9/32—Aligning or centering of the image pick-up or image-field
- G06K9/3233—Determination of region of interest
- G06K9/325—Detection of text region in scene imagery, real life image or Web pages, e.g. licenses plates, captions on TV images
- G06K9/3258—Scene text, e.g. street name
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
- G06K9/4633—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
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- G06K9/20—Image acquisition
- G06K9/32—Aligning or centering of the image pick-up or image-field
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- G06K9/3241—Recognising objects as potential recognition candidates based on visual cues, e.g. shape
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- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
- G06K9/00818—Recognising traffic signs
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- G06K9/00442—Document analysis and understanding; Document recognition
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- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
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- G06T2207/20—Special algorithmic details
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