Face Recognition Using Principal Component Analysis Applied to an Egyptian Face Database
Although face recognition is highly race-oriented, to-date there is no Egyptian database of face images for research purposes. This paper serves two purposes. First we present the efforts undertaken to build the first Egyptian face database (over 1100 images). Second we present a variant algorithm b...
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| creator | Ragab, Mohammad E. Darwish, Ahmed M. Abed, Ehsan M. Shaheen, Samir I. |
| description | Although face recognition is highly race-oriented, to-date there is no Egyptian database of face images for research purposes. This paper serves two purposes. First we present the efforts undertaken to build the first Egyptian face database (over 1100 images). Second we present a variant algorithm based on principal component analysis (PCA) but adjusted to Egyptian environment. In order to conduct face recognition research under realistic circumstances, no restrictions have been imposed on the volunteers (eyeglasses, moustaches, beards, and veils (hijab)). Furthermore, photos, for each volunteer, were taken during two sessions that are two months apart (March and May). Meanwhile, multiple light sources have been used. More than 1000 experiments have been carried out to evaluate the approach under different conditions. A new pentagon-shaped mask has been devised, which has proven suitable to enhance the recognition rate. |
| doi_str_mv | 10.1007/978-3-540-48765-4_58 |
| format | Conference Proceeding |
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This paper serves two purposes. First we present the efforts undertaken to build the first Egyptian face database (over 1100 images). Second we present a variant algorithm based on principal component analysis (PCA) but adjusted to Egyptian environment. In order to conduct face recognition research under realistic circumstances, no restrictions have been imposed on the volunteers (eyeglasses, moustaches, beards, and veils (hijab)). Furthermore, photos, for each volunteer, were taken during two sessions that are two months apart (March and May). Meanwhile, multiple light sources have been used. More than 1000 experiments have been carried out to evaluate the approach under different conditions. 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This paper serves two purposes. First we present the efforts undertaken to build the first Egyptian face database (over 1100 images). Second we present a variant algorithm based on principal component analysis (PCA) but adjusted to Egyptian environment. In order to conduct face recognition research under realistic circumstances, no restrictions have been imposed on the volunteers (eyeglasses, moustaches, beards, and veils (hijab)). Furthermore, photos, for each volunteer, were taken during two sessions that are two months apart (March and May). Meanwhile, multiple light sources have been used. More than 1000 experiments have been carried out to evaluate the approach under different conditions. A new pentagon-shaped mask has been devised, which has proven suitable to enhance the recognition rate.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Face Image</subject><subject>Face Recognition</subject><subject>Gray Level</subject><subject>Mahalanobis Distance</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Recognition Rate</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540660767</isbn><isbn>3540660763</isbn><isbn>9783540487654</isbn><isbn>3540487654</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1999</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNo9UU1LAzEQjV9gqf0HHnIQb9Fks9nNHkttVSgoYsFbmM2mS3SbxM320H9v-oEDwwxvHsO8NwjdMvrAKC0fq1ISTkROSS7LQpBcCXmGJgnmCTxg-TkasYIxwnleXfzPioKWRXmJRpTTjFRlzq_RJMZvmoJnIuUIfS1AG_xhtG-dHax3eBWta_F7b522ATo885vgnXEDnjrodtFGPA2hs6bBg8fg8LzdhcGm5rDqCQaoIZobdLWGLprJqY7RajH_nL2Q5dvz62y6JCETciCslg3otdQ63UsFz2XGQGjJDAUNjWxMOrQGUzYmiWMVbxgvkjBR1zUwo_kY3R_3ht7_bk0c1MZGbboOnPHbqDhjZVWIKhHvTkSIGrp1D0lgVKG3G-h3ismMZ3xPy460mCauNb2qvf-JilG1f4dK3iqukrvqYL3av4P_AY65eEo</recordid><startdate>1999</startdate><enddate>1999</enddate><creator>Ragab, Mohammad E.</creator><creator>Darwish, Ahmed M.</creator><creator>Abed, Ehsan M.</creator><creator>Shaheen, Samir I.</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>1999</creationdate><title>Face Recognition Using Principal Component Analysis Applied to an Egyptian Face Database</title><author>Ragab, Mohammad E. ; Darwish, Ahmed M. ; Abed, Ehsan M. ; Shaheen, Samir I.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p258t-1b8dacf8cc4060534821a5c81e0acad8de250bae7de334193d1366605bbba1ec3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Face Image</topic><topic>Face Recognition</topic><topic>Gray Level</topic><topic>Mahalanobis Distance</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Recognition Rate</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ragab, Mohammad E.</creatorcontrib><creatorcontrib>Darwish, Ahmed M.</creatorcontrib><creatorcontrib>Abed, Ehsan M.</creatorcontrib><creatorcontrib>Shaheen, Samir I.</creatorcontrib><collection>Pascal-Francis</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ragab, Mohammad E.</au><au>Darwish, Ahmed M.</au><au>Abed, Ehsan M.</au><au>Shaheen, Samir I.</au><au>El-Dessouki, Ayman</au><au>Ali, Moonis</au><au>Imam, Ibrahim</au><au>Kodratoff, Yves</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Face Recognition Using Principal Component Analysis Applied to an Egyptian Face Database</atitle><btitle>Lecture notes in computer science</btitle><date>1999</date><risdate>1999</risdate><spage>540</spage><epage>549</epage><pages>540-549</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540660767</isbn><isbn>3540660763</isbn><eisbn>9783540487654</eisbn><eisbn>3540487654</eisbn><abstract>Although face recognition is highly race-oriented, to-date there is no Egyptian database of face images for research purposes. This paper serves two purposes. First we present the efforts undertaken to build the first Egyptian face database (over 1100 images). Second we present a variant algorithm based on principal component analysis (PCA) but adjusted to Egyptian environment. In order to conduct face recognition research under realistic circumstances, no restrictions have been imposed on the volunteers (eyeglasses, moustaches, beards, and veils (hijab)). Furthermore, photos, for each volunteer, were taken during two sessions that are two months apart (March and May). Meanwhile, multiple light sources have been used. More than 1000 experiments have been carried out to evaluate the approach under different conditions. A new pentagon-shaped mask has been devised, which has proven suitable to enhance the recognition rate.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/978-3-540-48765-4_58</doi><tpages>10</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 1999, p.540-549 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_31179659 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Face Image Face Recognition Gray Level Mahalanobis Distance Pattern recognition. Digital image processing. Computational geometry Recognition Rate |
| title | Face Recognition Using Principal Component Analysis Applied to an Egyptian Face Database |
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