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High Occupancy Vehicle (HOV) and High Occupancy Tolling (HOT) lanes have been commonly practiced in several jurisdictions to reduce traffic congestion and promote car pooling. Camera-based methods have been recently proposed for a cost-efficient, safe and effective HOV/HOT lane enforcement with the prevalence of video cameras in transportation imaging applications. An important step in automated lane...
High Occupancy Vehicle (HOV) lanes encourage carpooling and have been a common method used by transportation agencies to reduce congestion on highways. Image-based enforcement for HOV lanes is an emerging technology that uses one or more cameras mounted on overhead gantries and/or roadside poles to capture imagery inside vehicles and make computer vision based assessments of the occupancy state of...
Commercial motor vehicles are mandated to display a valid U.S. Department of Transportation (USDOT) identification number on the side of the vehicle. Automatic recognition of USDOT numbers is of interest to government agencies for the efficient enforcement and management of the commercial trucks. Near infrared (NIR) cameras installed on the side of the road, to capture an image of an incoming truck,...
We propose a statistical script independent line based word spotting framework for offline handwritten documents based on Hidden Markov Models. We propose and compare an exhaustive study of filler models and background models for better representation of background or non-keyword text. The candidate keywords are pruned in a two stage spotting framework using the character based and lexicon based background...
Keyword spotting aims to retrieve all instances of a given keyword from a document in any language. In this paper, we propose a novel script independent line based word spotting framework for offline handwritten documents based on Hidden Markov Models. The methodology simulates the keywords in model space as a sequence of character models and uses the filler models for better representation of background...
In this work, we propose a novel multilingual word spotting framework based on Hidden Markov Models that works on corpus of multilingual handwritten documents and documents that contain more than one handwritten script. The system deals with large multilingual vocabularies without need for word or character segmentation. A keyword is represented by concatenating its character models. We propose and...
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