HUMAN MOOD DETECTOR BY USING DIGITAL IMAGE PROCESSING
The human face provides the most salient clue to person's emotional state. The face expressions are recognized -usingfeataies sueii as eye, eyebrow, mouth or nose. These features play a vital role in human mood recognition. This project, which is named as 'Human Mood Detector', wil...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Universiti Teknologi Petronas
2006
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| Online Access: | http://utpedia.utp.edu.my/6982/1/2006%20-%20HUMAN%20MOOD%20DETECTOR%20BY%20USING%20DIGITAL%20IMAGE%20PROCESSING.pdf http://utpedia.utp.edu.my/6982/ |
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| Summary: | The human face provides the most salient clue to person's emotional state. The face
expressions are recognized -usingfeataies sueii as eye, eyebrow, mouth or nose. These
features play a vital role in human mood recognition. This project, which is named as
'Human Mood Detector', will be recognizing a set of emotions, which consists of
angry, sad and happy, requiring vast of knowledge in Digital Image Processing.
These projects ate divided into two categories, software development in the first
semester, and implementation in the next semester. The identification of& person's
mood is based on input from digital camera. Then, the input image will be undergo
digitization, noise removal, resizing, format transformation, contrast enhancement,
segmentation and feature extraction. Veatuie extraction is a crucial stage in this
system; since at this stage; the important feature information from the image will be
extracted, which will lead to the desired result A few distinct criteria that will
distinguish the emotion are recognized, using segmented images of mouth, forehead
or eye shape. These distinct criteria will he used to develop an algorithm that
differentiates all the three emotions described before. To classify a person's mood, a
similarity matching procedure will be performed from the input image whereby the
input will be matched with the set of criteriathat has been classified in the program.
Thirty images nmU be Tased in the second semester ^witfe different set of mood for
testing. If, the eKtracted information falls within the classified features of a certain
mood, the mood of the person will be identified. Identification result will be
presented at the end withthe probability. Thetheory, concept, proposed methodology
as well as softwaredevelopment (coding) arerepresented in this report. |
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