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008			220204s2022 si | s |||| 0|eng d
020			_a9789811690419
024	7		_a10.1007/978-981-16-9041-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1654 _b2022 EB
100	1		_aSoni, Badal _eautor _0(orcid)0000-0002-9617-9468 _1https://orcid.org/0000-0002-9617-9468 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683598
245	1	0	_aImage Copy-Move Forgery Detection : _bNew Tools and Techniques _cby Badal Soni, Pradip K. Das
250			_aFirst edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XXI, 133 páginas) _b66 ilustraciones, 60 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aStudies in Computational Intelligence _x1860-9503 _v1017
505	0		_aIntroduction -- Background Study and Analysis -- Copy-Move Forgery Detection using Local Binary Pattern Histogram Fourier Features -- Blur Invariant Block-based CMFD System using FWHT Features -- Geometric Transformation Invariant Improved Block based Copy-Move Forgery Detection -- Key-points based Enhanced Copy-Move Forgery Detection System using DBSCAN Clustering Algorithm -- Image Copy-Move Forgery Detection using Deep Convolutional Neural Networks.
520			_aThis book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.
988			_aSpringer_Engineering_2022
650		7	_2embne _9413188 _aProceso digital de imágenes
650		7	_2embne _9141254 _aDelitos informáticos
700	1		_aDas, Pradip Kumar _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9682057
776	0	8	_iPrinted edition: _z9789811690402
776	0	8	_iPrinted edition: _z9789811690426
776	0	8	_iPrinted edition: _z9789811690433
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-9041-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b04/2022 _dz _esc _zSI