1. WHAT IS YOUR RACE ?: ETHNICITY AND RACE IDENTIFICATION IN MYANMAR
Presented By:
Ms. Hlaing Htake Khaung Tin
University of Computer Studies, Yangon, Myanmar

2. WHAT IS YOUR RACE ?

3. ETHNICITY AND RACE IN MYANMAR
Myanmar is one of the most ethnically diverse countries in the world.

4. Introduction
People who have heard of Myanmar know it as "the Land of Pagodas" or "Golden Land".
Almost 90 percent of Myanmar's population practices Buddhism, a major religion with some 300 million followers worldwide.
Thanks to the predominance of Buddhism, the tourist will find himself choosing between thousands of temples and shrines.

5. Cont’d
Today the country has a population of 53 millions people, neighboring Thailand, Laos, Bangladesh, India and China.
With an area of square kilometers (261,228 square miles), Myanmar is the largest country in the South East Asian peninsula - almost three times the size of Britain.
In the north and east it borders on China, Laos and Thailand, and in the west on Bangladesh and India while the southern coast lies on the Bay of Bengal and the Andaman Sea.
The main rivers are the Ayeyarwady (Irrawaddy) ,Chindwin, Thanlwin (Salween) and Sittaung.

6. List of ethnic groups in Myanmar
Myanmar is an ethnically diverse nation about over 100 distinct ethnic groups officially recognized by the Myanmar government. These are grouped into eight "major national ethnic races":
Kachin
Kayar
Kayin
Chin
Mon
Bamar
Rakhine
Shan
The "major national ethnic races" are grouped primarily according to region rather than linguistic or ethnic affiliation.

7. Rough Estimation of Ethnic in Myanmar

8. Definition of Category
Racial Category
Definition of Category
Kachin
Kachins live in Kachin State in the northernmost past of Myanmar, They are well-known for their fierce fighting spirit, as are the Chin people.
Kayar
Kayar people were once known as Red Kayin (Karenni) and live in Kayah State, south of Shan State.
Kayin
Kayin (Karen) are the third largest group; Sgaw and Pwo Kayins are the two main Kayin groups. They live in the Ayeyarwady delta and also in hilly Kayin State.
Chin
The Chin people live in Chin and Rakhine state. About percent of the Chin have converted to Buddhism and Christianity; the rest are animists; that is, they worship spirits.
Mon
Mon people settle in Ayeyarwaddy delta, Mon state, and Karen state. One of the earliest peoples to reside in Southeast Asia, the Mon were responsible for the spread of Theravada Buddhism in Myanmar and Thailand.
Barmar
Bamars, or ethnic Myanmar, are the largest ethnic group, comprising 68 percent of the total population. Referred to generally as Myanmar, as opposed to the other ethnic groups, Bamars are basically mixed with Mons, and the Tai Shan.
Rakhine
Roughly 3 millions Arakanese or Rakhine people have resided along the western coast of Myanmar. Like Bamar and Mons, Rakhine people are Buddhists, and their language are similar to Bamar.
Shan
The Shans, light skinned and tall, are related to the Thais and the people of Laos. Primarily farmers, they live in the river valleys and lowland pockets of the Shan plateau, forming 9 percent of the total population.

9. Definition of the Problem
Implementing algorithms that enable the identification of a person’s race or ethnic; based on features derived from his/her face image.
Race/ Ethnic
Kachin
Kayar
Kayin
Chin
Mon
Bamar
Rakhine
Shan
Race= ?

10. Database Specifications
Age
0 to 70
Female, Male
70%, 30%
Kachin 50
Kayar 40
Kayin
Chin
Mon 30
Bamar 70
Rakhine 60
Shan
Resolution
250 * 250
Greyscale

11. Own Demographics
400 images of 400 subjects

12. Steps in Race Identification
Test Image
Input Face Database
Match from Database
Comparison Tests
Top Eigenfaces
Eigenface Database

13. Race Identification System
Noise filtering, face region detection, extracted region cropping and image adjusting processes are included in this process.
Within a given database, all weight vectors of the persons within the same race group are averaged together.
This creates “a face class”.
When a new image comes in, its weight vector is created by projecting it onto the face space.
The face is then matched to each face class that gives the minimum Euclidean distance.
A ‘hit’ is occurred if the image nearly matches with its own face class.
And then the age group that gives the minimum Euclidean distance will be assumed as the age of the input image.

15. Traditional Dresses for Some Races

16. Author’s Publication
[1] Hlaing Htake Khaung Tin, “Facial Extraction and Lip Tracking Using Facial Point”, International Journal of Computer Science and Engineering and Information Technology (IJCSEIT), vol.1, no.1, April (India)
[2] Hlaing Htake Khaung Tin and Myint Myint Sein, “Fast Facial Recognition System”, IEEE The proceeding of the 8th International Joint Conference on Computer Science and Software Engineering (JCSSE 2011), May (Thailand)
[3] Hlaing Htake Khaung Tin and Myint Myint Sein, “Effective Method of Age Dependent Face Recognition”, The proceeding of International Conference on Computer Science and Informatics (ICCSI 2011), June (India)
[4] Hlaing Htake Khaung Tin and Myint Myint Sein, “Effective Method of Age Dependent Face Recognition”, International Journal of Computer and Informatics (IJCSI), vol.1, issue.1, June (India)
[5] Hlaing Htake Khaung Tin and Myint Myint Sein, “Race Identification from Face Images”, The proceeding of International Conference on Advances in Computer Engineering (ACE 2011), August (India)

17. Cont’d
[6] Hlaing Htake Khaung Tin and Myint Myint Sein, “Race Identification from Face Images”, International Journal on Information Technology (IJIT), vol.1, issue.2, August (India)
[7] Hlaing Htake Khaung Tin and Myint Myint Sein, “Robust Method of Age Dependent Face Recognition”, IEEE the 4th International Conference on Intelligent Networks and Intelligent Systems (ICINIS 2011), November (China) (Best Paper Award Achievement)
[8] Hlaing Htake Khaung Tin and Myint Myint Sein, “Developing the Age Dependent Face Recognition System”, International Journal of Intelligent Engineering and Systems (IJIES), vol.4, issue.4, December (China)
[9] Hlaing Htake Khaung Tin and Myint Myint Sein, “Aging Groups Classification based on Facial Feature”, The proceeding of International Conference on Information Technology Management Issues (ICITMI 2011), September (Malaysia)
[10] Hlaing Htake Khaung Tin and Myint Myint Sein, “Aging Group Classification based on Facial Feature”, Journal of Information Systems : New Paradigms (JISNP), vol.1, no.1, September (Malaysia)

18. Cont’d
[11] Hlaing Htake Khaung Tin, “Perceived Gender Classification from Face Images”, International Journal of Modern Education and Computer Science (IJMECS), vol.4, no.1, February (Hong Kong)
[12] Hlaing Htake Khaung Tin, “Robust Algorithm for Face Detection in Color Images”, International Journal of Modern Education and Computer Science (IJMECS), vol.4, no.2, March (Hong Kong)
[13] Hlaing Htake Khaung Tin, “Subjective Age Prediction of Face Images Using PCA”, International Journal of Information and Electronics Engineering (IJIEE), vol.2, no.3, May (Singapore)
[14] Hlaing Htake Khaung Tin, “Gender and Age Estimation Based on Facial Images”, International Journal : ACTA TECJNICA NAPOCENSIS Electronics and Telecommunications, vol. 52, no.3, (Romania)
[15] Hlaing Htake Khaung Tin, “Feature based Age Prediction for Face Recognition”, The 5th Parallel and Soft Computing (PSC 2010), December (UCSY)

19. Cont’d
[16] Hlaing Htake Khaung Tin and Myint Myint Sein, “Automatic Aging Simulation of the Human Face”, The 9th International Computer Applications (ICCA 2011), May (Myanmar)
[17] Hlaing Htake Khaung Tin, “Removal of Noise Reduction for Image Processing”, The 6th Parallel and Soft Computing (PSC 2011), December (UCSY)
[18] Hlaing Htake Khaung Tin, “Automatic Age Prediction of Aging Effects on Face Images”, The 10th International Computer Applications (ICCA 2012), February (Myanmar)
[19] Hlaing Htake Khaung Tin, “Personal Identification and Verification using Palm Print Biometric”, The 3rd International Conference on Advancement of Engineering (ICAE 2012), December (India)
[20] Hlaing Htake Khaung Tin, “Personal Identification and Verification using Palm Print Biometric”, International Journal of Latest Technology in Engineering Management and Applied Science (IJLTEMAS), vol. 1, issue. X, December (India)

20. Cont’d
[21] Hlaing Htake Khaung Tin, “Effective Method of Face Recognition and Palmprint Biometrics for Personal Identification”, International Journal of Advanced and Innovative Research (IJAIR), December (India)
[22] Hlaing Htake Khaung Tin, “Age Dependent Face Recognition using Eigen Face”, International Journal of Modern Education and Computer Science (IJMECS), vol.5, no.9, October (Hong Kong)
[23] Hlaing Htake Khaung Tin, “How Old Are You?: Age Prediction using Eigen Face”, The 4th International Conference on Science and Engineering (ICSE), December (Myanmar)

21. Conclusion Race is classified differently depending on culture.
Race identification plays an important role in face-related applications.
Experimental results are indicated that participants categorized the race of the face and this categorization drives the perceptual process.
A face image data set is collected from Internet, and divided into a training dataset and a test dataset.
The dataset is separated into eight race groups, Kachin, Kayah, Kayin, Chin, Mon, Bamar, Rakhine and Shan.
These face images are contained variations in pose, illumination and expression.
We have another plan to use racially ambiguous faces which involve participants of other races.

22. Thank You Very Much For Your Attention!