Department of Computer Science and Engineering

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Browsing Department of Computer Science and Engineering by Author "Bulugu, Isack"

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    Algorithm for License Plate Localization and Recognition for Tanzania Car Plate Numbers
    (International Journal of Science and Research, 2013-05) Bulugu, Isack
    In this paper, License plate localization and recognition (LPLR) is presented. It uses image processing and character recognition technology in order to identify the license number plates of the vehicles automatically. This system is considerable interest because of its good application in traffic monitoring systems, surveillance devices and all kind of intelligent transport system. The objective of this work is to design algorithm for License Plate Localization and Recognition (LPLR) of Tanzanian License Plates. The plate numbers used are standard ones with black and yellow or black and white colors. Also, the letters and numbers are placed in the same row (identical vertical levels), resulting in frequent changes in the horizontal intensity. Due to that, the horizontal changes of the intensity have been easily detected, since the rows that contain the number plates are expected to exhibit many sharp variations. Hence, the edge finding method is exploited to find the location of the plate. To increase readability of the plate number, part of the image was enhanced, noise removal and smoothing median filter is used due to easy development. The algorithm described in this paper is implemented using MATLAB 7.11.0(R2010b).
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    An Improved Method for Tanzania Number Plate Location and Segmentation Based on Mathematical Morphology and Regional Features of an Image
    (International Journal of Science and Research, 2013-12) Bulugu, Isack; Zhijun, Pei
    In the Automatic Number Plate Recognition System (ANPR), Plate Number Location and Character segmentation are very important parts of an ANPR system before Recognition part. In this paper, plate number localization and character segmentation using mathematical morphological approach and regional features of images are discussed from the proposed ANPR system of vehicles in Tanzania. The proposed algorithm consists of three main modules: Pre-processing (cutting and resizing, convert RGB image to grayscale image, image binarization use Otsu method), Finding Region of Interest(morphology opening to remove noises & dilation operation, measure properties of image regions to find candidates), License plate exactly location (finding the LP angle & rotating LP, cut exactly LP region). The Character segmentation also consist three parts: Eliminate incrimination of the binary using boundary features, removes impurities using regional features and morphological process, and divide character into sub-images. The results show an average of 98% successful plate number localization and segmentation for proposed ANPR system in a total of 200 images captured from a complex outdoor environment in Tanzania. Implementation was done using MATLAB Version 7.11.0 (R2010b).
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    Scale Invariant Static Hand-postures Detection using Extended Higher-order Local Autocorrelation Features
    (Foundation of Computer Science, 2016-02) Bulugu, Isack; Ye, ZhongFu
    This paper presents scale invariant static hand postures detection methods using extended HLAC features extractedfrom Log-Polar images. Scale changes of a handposture in an image are represented as shift in Log-Polar image. Robustness of the method is achieved through extracting spectral features from theeach row of the Log-Polar image. Linear Discriminant Analysis was used to combine features with simple classification methods in order to realize scale invariant hand postures detection and classification.The method was successful tested by performing experiment using NSU hand posture dataset images which consists 10 classes of postures, 24 samples of images per class, which are captured by the position and size of the hand within the image frame. The results showed that the detection rate using ExtendedHLAC can averaged reach 94.63% higher than using HLAC features on a Intel Core i5-4590 CPU running at 3.3 GHz.
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    Web-Accessible Liquid Distillation Column Temperature Monitoring and Control using ilab Shared Architecture
    (2013) Bulugu, Isack; Mwambela, Alfred
    The liquid distillation column is a research facility used in chemical and processing engineering at University of Dar es salaam. Originally it has been manually operated require the presence of operators all-time. It is used to control and take measurements data under hazardous operating condition. In this work the research equipment has been automated and its control and monitoring can now operate online, hence shared by many researchers. In this paper, the major findings were data acquisition device (DAQ) NI USB 6211 for acquiring temperatures and generate signals for control purposes, and thermocouples type K sensors were used since they can operate at very wide temperature range of -270 to 1370. The main parameter which has been monitored is temperature at various parts of the distillation column including temperature of the top/bottom and reboiler temperature. The approach used was computer controlled using Data acquisition device and labVIEW graphical programming language as standalone control system to extent it control and monitoring temperature online. The Interactive ilab shared architecture has been used to make the system accessible remotely. Labserver was created then interfaced with distillation column using NI USB 6211 as a data acquisition device. The DAQ was configured for temperature acquisition and signal generation for monitoring temperature and flux flow control respectively. For the remotely operation, the Labserver was connected to the LAN/internet and the distillation column was accessed through web services.