StableCode 24-hours Hackathon

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ELGC

sabaraheem

System will be based on image processing techniques. Recognition of facial expressions is targeted in order to improve the autism patient’s emotional understanding. To build software which involves image processing mechanism where training is performed on various facial expressions and then they are tested to recognize desired expression. Our Goal of this project to judge the expressions of autism patients in easiest way who can’t express his feelings. We will make this project to detect the feeling of all these and to help them.

•	First, the app will start and ask user to capture or browse image.
•	Then app will convert an RGB image to greyscale/Bitmap and apply 
        noise reduction techniques.
•	After that, app will detect image and extract required features to 
        create facial expressions.
•	Then using mood classifiers, it will generate a model.
•	After that generated model will be matched to trained data using 
        cognitive analysis.
•	If model matches then app will generate an alert about mood 
        detection.
•	At last, detected mood will be tested.
High-level system components:
•	Capturing & Browsing of Image
•	Noise Reduction
•	Grey Scale Conversion
•	Image processing & Edge Detection
•	Analyzing Image matching
•	Mood Detection


The system will maintain a dynamic source of picture and after applying image processing techniques it will generate the models to classify them into different moods. Moreover, research will be performed to define a mood for detecting autism in patients.

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