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Re-Identification of Vehicles by License Plate Recognition
Špaňhel, Jakub ; Juránková, Markéta (referee) ; Herout, Adam (advisor)
This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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Modal Split in Major Czech Cities: Thorough Analysis and Proposal of Policies Leading to Less Car-Dependent Urban Mobility
Bystřický, Vojtěch ; Ščasný, Milan (advisor) ; Šťastná, Lenka (referee)
This thesis focuses on examining the modal split in the five largest Czech cities. Using data from the first nationwide survey on travel behavior in the Czech Republic called Česko v pohybu, the author identifies the main factors which influence the mode choice of inhabitants of Czech cities. The data were evaluated using multinomial logistic regression. Since modal split studies of a large extent are mostly conducted in Western Europe, the United States or Asia-Pacific region, the main contribution of this thesis is to shed some light also on the travel behavior in the Central Europe, more precisely in the largest cities of the Czech Republic. The author analyzes the impact of socio-demographic variables, such as the respondents' age, education level or household income, as well as the importance of the variables related to the trip, such as trip purpose or trip distance. Further, the author also provides comparison of the travel behavior between the examined cities. Among other findings, the author finds that the entitlement to discounted public transport coupons through the ownership of a discount card does not have a significant effect on the probability of using public transport. Further, the results also show that higher education level does not lead to greater use of ecologically friendly...
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Re-Identification of Vehicles by License Plate Recognition
Špaňhel, Jakub ; Juránková, Markéta (referee) ; Herout, Adam (advisor)
This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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