Real time motorcycle image detection and analysis

This research investigated image tracking and edge detection for motorcycle in various lighting and weather conditions. The capability in different resolution and threshold level also evaluated. Comparison between hardware and software implementation of edge detection also been made. Develop framework showed great accuracy is segmentation of plate number from motorcycle image in daylight condition compared to rainy daylight and night condition. The aim of this project is to develop framework for motorcycle image detection and recognize for traffic offender. Analysis with histogram level and contrast stretching method showed performance in hardware is improved rather than software

Motorcycle image application on MATLAB Simulink and FPGA platform

This research investigated image tracking and edge detection for motorcycle in various lighting and weather conditions. The capabilities in different resolutions and thresholds level also evaluated. Comparison between hardware and software implementation of edge detection also been made. Developed framework showed great accuracy in segmentation of plate number from motorcycle image in daylight condition compared to rainy daylight and night condition

Real-time motorcycle image detection and histogram analysis of plate recognition enhancement

This research investigated of image tracking and edge detection for motorcycle in various lighting and weather conditions. The capability in different resolution also evaluated. The developed framework showed great accuracy in the segmentation of plate number from motorcycle image in daylight condition as compared to rainy daylight and night condition. A benchmark study was conducted to identify fast processing time in the system. MATLAB-Simulink and Xilinx System Generator prototyping environment were selected for designing the detection system. The detection system was implemented on Field Programmable Gate Array (FPGA/hardware) and MATLAB (software). Images were analyzed by comparing the accuracy of bounding box and edges which is displayed in different conditions, different threshold level, different resolutions and different distances. The output image is clear with pixel 1024 x768 in daylight, rainy and night. The performance of image output is drop and blur while used low pixel resolutions such as 640 x 480, 720 x 480 and 800 x 600. Motorcycle plate number is recognized in daylight condition at 5.0 meter. The analysis showed daylight is the best situation in detecting the motorcycle image followed by rainy daylight condition and night. Analysis with Histogram level and contrast stretching method showed performance in hardware is improved rather than software. This project can be applied to improve the visual driver support system in the future

Integration of PECOS into MARMOT for embedded real time software component-based development

In ERT (Embedded Real Time) software development, software functionality is not the only focus but multi-constraints extra-functionality requirement such as timing, resources constraint, statically predictable, safetycritical, processing power and memory is also important. Besides that, ERT software development involves multidisciplinary knowledge that includes software, mechanical and electronic engineering fields. To meet these two challenges ERT software development must be able to support the multiconstraint and multi-disciplinary challenges. From this perspective, CBD (Component-Based Development) appears to be one of the appropriate approaches to design the ERT software due to the ability of domain experts to interactively compose and adapt sophisticated ERT software which the decrease of development time and improvement of software quality. Existing component infrastructures used in ERT software development are MARMOT (Component-Based Real-Time Object-Oriented Development and Testing) and PECOS (Pervasive Component System). However, these technologies are not enough to support the two challenges in their CBD activities. This paper discusses about the integration of PECOS and MARMOT by mapping the metamodel of the two technologies and proposing a process model. The aim of the integration is to support methodological CBD software to enable systematic development of ERT software with consideration of multi-disciplinary knowledge and multiconstraint

Motorcycle image analysis with nanoelectronics platform

This research investigated of image tracking and edge detection for motorcycle in various lighting and weather conditions with nanoelectronics platform. The platform capability in different resolution and threshold level also evaluated. Comparison between field programmable gate array (FPGA) hardware platform and (MATLAB) software platform has been made. Developed framework showed great accuracy in segmentation of motorcycle plate number in daylight compared to rainy daylight and night condition. System developed has the processing time less than 40 milliseconds in various critical conditions such as daylight, rainy daylight and night conditions. The output image was analyzed by comparing the accuracy of bounding box and edges which is displayed in different conditions, threshold level, resolutions and distances. The result showed different performance for each condition. The output image is clear with pixel 1024 x768 in daylight, rainy and night. Meanwhile image quality getting blur while used low pixel resolutions such as 640 x 480, 720 x 480 and 800 x 600. Total speed for each image processing is 30 frames per second. The ability of this system captured motorcycle image is 5 to 15 meter in daylight, rainy and night. Analysis with Histogram level and contrast stretching method showed performance in hardware is improved rather than software [1-6]