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

WHAT IS YOUR RACE ?

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

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.

Cont’d Today the country has a population of 53 millions people, neighboring Thailand, Laos, Bangladesh, India and China. With an area of 676.577 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.

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.

Rough Estimation of Ethnic in Myanmar

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 80-90 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.

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= ?

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

Own Demographics 400 images of 400 subjects

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

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.

Traditional Dresses for Some Races

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 2011. (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 2011. (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 2011. (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 2011. (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 2011. (India)

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 2011. (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 2011. (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 2011. (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 2011. (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 2011. (Malaysia)

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 2012. (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 2012. (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 2012. (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, 2011. (Romania) [15] Hlaing Htake Khaung Tin, “Feature based Age Prediction for Face Recognition”, The 5th Parallel and Soft Computing (PSC 2010), December 2010. (UCSY)

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 2011. (Myanmar) [17] Hlaing Htake Khaung Tin, “Removal of Noise Reduction for Image Processing”, The 6th Parallel and Soft Computing (PSC 2011), December 2011. (UCSY) [18] Hlaing Htake Khaung Tin, “Automatic Age Prediction of Aging Effects on Face Images”, The 10th International Computer Applications (ICCA 2012), February 2012. (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 2012. (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 2012. (India)

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 2012. (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 2013. (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 2013. (Myanmar)

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.

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