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Register a new userDesign Lab Model to Automate Four Traffic Jams using Image Processing
تصميم نموذج مخبري لاتمتة اربع عقد مرورية باستخدام معالجة الصورة
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Added by
Tartous University رسالة ماجستير
Publication date
2016
fields
Informatics Engineering
and research's language is
العربية
Created by
Shamra Editor
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يقدم البحث تصميم نموذج مخبري لأتمتة أربع عقد مرورية باستخدام معالجة الصورة - مقترحا لنظام مروري مؤتمت مرئيا. وذلك بتنظيم عمل عقدة مرورية اعتماداً على المعالجة الرقمية لصور أربع كاميرات مركبة على التقاطع.
The research presents the design of a laboratory model to automate four traffic nodes using image processing - a proposal for a visual automated traffic system. By organizing the work of a traffic node, depending on the digital processing of the images of four cameras installed at the intersection.
References used
R.Baskara, P. Dhavachelvan "Automated Traffic Signal System based on Traffic by Tracking Objects:
rate research
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This research serves the process of organizing the traffic by reducing traffic congestion,
especially at peak times to a minimum, presenting an effective method is not used locally to
automate traffic lights adoption concepts, image processing, con
trollers, communication. It is
organizing image capture processes on a regular basis in all the streets leading to the traffic
node, and then this image was taken to the central computer, which is processes each image by
comparing them with all the pictures taken at a certain moment and based on the comparison, the
Central Computer conclusion of the new chronological order to change traffic lights in all the
streets then sends the new update to the controllers in each signal light which leads to re-
Automatics these signals,by reducing bottlenecks to the minimum level and repeat imaging
processes and modernization of signals throughout the day we can have access to a system to
automate the traffic contract is close to the ideal note that by connecting traffic contract with
each other and with the main central computer we can solve other problems like emergency and
firefighting.
Key words: a traffic node, signal processing, camera, network, processor, microcontroller.
The various types of radial distortions generated by digital cameras are presented in this paper, like Barrel Distortions and Pincushion Distortion.
Image processing techniques are used to correct the barrel distortion generated by wide-angle lenses
of digital cameras. A model for barrel distortions is founded. Moreover, an algorithm for correcting this distortion is developed. This algorithm depends on finding the right parameters of the model. The grid pattern is used to detect pixels that caused the distortion and reallocate these pixels back into their original locations, making the corrected photo as close as possible to the original.
This paper presents an algorithm for designing a system that classifies standard
human facial expressions which are fear, disgust, sad , surprise, anger, happiness, and the
normal expression . The facial expression that is presented in the input im
age of the system
can be classified depending on extracting appearance features then, it is entered into
neural network to complete the classification process using Matlab as a programming
language.
Multiple stages completed the work, which are, (collection images, pre-processing of
the images, feature extraction, training neural network, classification and testing). Our
system has been able to achieve the highest rating when the expression of anger reached
100 %, while the lowest rating was at the expression of sad by 30%.
This paper presents an algorithm for designing a system that classifies standard human facial expressions which are fear , disgust , sad , surprise , Anger , happiness , natural expression . The facial expression that is presented in the input image
of the system can be classified depending on extracting appearance features , then they entered into neural network to complete the classification process using Matlab as a programming language.
This research aims to developing new method for breast tumors extraction and
features detection in breast magnetic resonance images by depending on clusteringand
image processing algorithms. At the beginning, one of clustering algorithms was used f
or
image segmentation and grouping pixels by their gray scale values. Then morphological
operations were implemented in order to remove noise and undesired regions, after that
suspected areas were extracted. Finally some shape features for extracted area were
detected, this features could be very useful for tumors diagnosis. A database consisted of
96breast magnetic resonance images were used and proposed approach was appliedby
MATLAB program, and we obtainedbreast tumors extraction and its features and
compared them with the doctor's opinion .
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