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Content-based direct access methods for face recognition biometric system: State of the art
Pahendra I.a,b, Sitohang B.a, Akbar S.a
a Data and Software Engineering Research Division, School of Electrical Engineering and Informatics, Institut Teknologi Bandung Jl, Bandung, West Java, Indonesia
b Department of Electrical Engineering, Sriwijaya University Jln. Palembang Prabumulih, Indralaya, South Sumatra, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2006-2015 Asian Research Publishing Network (ARPN).As a biometric component, the human face has a unique information and characteristics that are invariant, so this allows the system to do a face search by utilizing the original information that is attached to the face that is unique internal characteristics of the extraction face, no longer use alphanumeric keyword to search-based face. In the conventional method, the process of searching is dominated by the use of external attributes as keywords and as a basis for classification. The use of visual attributes as a keyword is the latest method in this field. In this research a short explanation about various face recognition methods and application are given. A state of the art of content-based direct access methods for face detection is also explored. A future work on these research areas are given as a guide for other researcher to make an advanced research in the future.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Biometric,Direct access methods,Feature extraction,Non alphanumeric[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]