Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userAutomatic Facial Expression Classification Using Image Processing Technique ( Fear – disgust – sadness – Surprise – Anger – Happiness – Natural )
التصنيف الآلي لتعابير الوجه باستخدام تقنيات معالجة الصورة (الخوف – الاشمئزاز – الحزن – التفاجؤ – الغضب – السعادة – التعبير الطبيعي)
2885
2 103
0
(
0
)
Created by
Shamra Editor
Ask ChatGPT about the research
يقدم هذا البحث خوارزمية لتصميم نظام يقوم بتصنيف التعابير القياسية السبعة لوجه الإنسان (الخوف – الاشمئزاز – الحزن – التفاجؤ – الغضب – السعادة – التعبير الطبيعي) باستخدام بعض تقنيات معالجة الصورة، حيث يتم تصنيف تعبير الوجه الموجود في الصورة المدخلة للنظام بالاعتماد على استخلاص سمات المظهر من الوجه المعتبر و إدخالها إلى شبكة عصبونية لإتمام عملية التصنيف و ذلك باستخدام لغة البرمجة Matlab. تم إنجاز العمل على مراحل متعددة و هي: (مرحلة تجميع الصور، مرحلة المعالجة المسبقة للصورة، مرحلة استخلاص السمات، مرحلة تدريب الشبكة العصبونية، مرحلة التصنيف و الاختبار). و قد تمكن نظامنا المعتبر من تحقيق أعلى نسبة تصنيف عند تعبير الغضب حيث وصلت 100% , بينما أدنى نسبة تصنيف كانت عند تعبير الحزن و هي 50%.
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 image 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%.
References used
C. C. Chibelushi , F. Bourel , Facial Expression Recognition: A Brief Tutorial Overview, School of Computing, University, 2002
S. Moore, R. Bowden , Local binary patterns for multi-view facial expression recognition , / Computer Vision and Image Understanding 115 (2011) 541–558,2011
K. Mehotra, , C. K. Mohan and S. Ranka, , Self-Organizing Maps (SOMs) , Prentice Hall. pp. 169-187
rate research
Read More
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.
With the increase in social networks, people have started to share information via different types of social media. Among themwere sites for exchanging people's opinions and others to exchange stories about real life and stories for children. In this
work we made use of children's stories and employed them to teach children with Down syndrome the correct feelings by reading a story for them, converting it into text, processing the text using natural languages and extracting feelings automatically from This story, and to achieve this, we used several techniques, combined them, and compared their results on a number of short stories dedicated to children, where each of the different techniques that were unsupervised, such as Dictionary Based or supervised, such as data-dependent neural networks, were used to analyze feelings, where we used multiple classifiers. They are Support Vector Machine, Stochastic Gradient Descent, Decision Tree, Random Forest, Naïve Bayes, K-Nearest Neighbor, and Nearest Centroid We also used deep neural networks as the example of RNN. Finally, the correct sentiment for the story was reached through Dictionary Based which gave the best accuracy and then showed a photo that shows the child the expression they want to start with The events of this story to interact with him and learn the correct expression
This Paper offers an effective method to measure the length of the
femur in Fetal Ultrasound Images, it applies a series of steps
starting with the reducing amount of noise in these images, and
then converted them to a binary form and uses morphol
ogical
operations to segment the femur and isolate it from the rest of the
image objects, then it applies an Edge Detector in order to find the
edges of the bone, then uses the Hough Transform to detect straight
lines in the image. we apply overlapping for resulted lines on the
original image, finally we choose the most significant and longest
straight line which is corresponding to the length of the femur. The
proposed method facilitates the measurement of the femur without
the help of a physician through a series of steps.
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 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.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
