An improved Malaysian automatic license plate recognition (M-ALPR) system using hybrid fuzzy in C++ environment

In this paper, an improved hybrid fuzzy technique (Fuzzy Logic and Template matching) for Malaysian Automatic License Plate Recognition (M-ALPR) system is proposed. The system is proposed to reduce the program complexity of the existing M-ALPR system and to decrease the processing time of recognizing Malaysian license plates. First, the algorithm to recognize the license plates is presented, by taking advantage of Matlab and C++ programming language benefits in order to increase system efficiency. Feature extraction using vertical line counter is introduced in this system. Later, with the help of OpenCV, the hybrid fuzzy technique is developed using the C++ language. Then, the comparison between these two implementations on M-ALPR system was reported. The improved system was tested on 740 samples images from real scene and the results show that the proposed improvement supports the accurateness and high speed processing of M-ALPR system

Real-time Malaysian automatic license plate recognition using hybrid fuzzy logic with skew detection and correction method

Automatic License Plate Recognition (ALPR) system is a mass surveillance method that uses optical character recognition on images to read the license plates on vehicles. This system has been used widely overseas. However, the different forms of Malaysian license plates still a problem that makes this system harder to be applied locally. The proposed license plate recognition algorithm is aimed to recognize the different Malaysian license plates by employing two methods: Fuzzy Logic to recognize standard license plate (the plates which consist of characters and numbers), and Template Matching to recognize non-standard plates (the plates which consist of non-standard word and numbers). Mathematical Morphology is the first preprocessing step used to enhance Malaysian license plate image quality, by removing noise from the binarized image. The second step is to remove license plate borders by implementing Mathematical Morphology process with conditional statements. The third preprocessing step is a new Skew Detection and Correction (SDC) method proposed to correct the skewness of license plate image. License plate level testing follows the preprocessing step in order to check if the license plate is one or two rows (the license plate elements are in one or two rows). The standard and non-standard test is performed by checking if the input image is representing a standard or a non-standard plate. Vertical scanning (VS) and horizontal scanning (HS) have been used to segment license plate image elements. Segmentation process is the step where license plate elements are segmented. The next step is to forward the extracted characters and numbers to the Fuzzy Logic system to be recognized in case of standard license plates input, while forward nonstandard words images to the Template Matching in order to be recognized in case of non-standard license plates input. The output of recognition step will be a string of numbers and characters which represent the recognized license plate. The proposed M-LPR algorithm has shown an impressive result to recognize different Malaysian license plate forms. Fuzzy Logic system has been tested on standard license plate shows 92.16% recognition accuracy and 0.88 second processing time. The Template Matching shows 92% recognition accuracy and 1.06 second processing time when it is tested on non-standard license plate. The proposed SDC method has been evaluated by comparing with different other existing SDC methods such as Hough Transform, Projection Profile, Mathematical Morphology and Bounding Box methods

Development of liquid sequencing valves by controlling air-flow to perform biomedical processes on centrifugal microfluidic platforms / Wisam Salah Hussein Al Faqheri

This thesis presents three different liquid valving methods for the centrifugal microfluidic platform, namely vacuum/compression wax valve, passive liquid valve (PLV), and check valve. The mechanism of the proposed valves is simply based on sequencing the liquid flow by controlling air-flow inside the microfluidic network. Specifically, the wax valve and passive liquid valve utilize a volume of trapped air in the source chamber or the destination chamber to control the burst frequency of the liquid. In contrast, the check valve controls the direction of the air to control the flow direction of the pumped liquid. Compared with the previously proposed valves, this mechanism prevents any direct contact between the valving materials and the sample/reagents. This will reduce the chance of sample/reagents contamination, and allow the use of wider range of valving materials. As a proof of concept, liquid metering, liquid switching, and liquid swapping are conducted using the proposed valving methods. Furthermore, Bradford assay for protein concentration detection, and enzyme linked-immunosorbent assays (ELISAs) for dengue are demonstrated to show the capability of the developed valves to perform biomedical applications. The results illustrate that the valves reduce the required spinning frequency to perform the microfluidic processes on the centrifugal platforms. In addition, the presence of physical barriers improves the ability of the developed valves to reduce vapour and contamination effect. Furthermore, the proposed valves show additional advantages such as the simplicity of fabrication and implementation, reversibility and multi-actuation, and compatibility with biomedical applications. Finally, the demonstration of the ELISA and the Bradford assays illustrate the ability of the presented valves to be integrated in any multistep biomedical and chemical application on the centrifugal microfluidic platform