國立虎尾科技大學 |

Context Based Tattoo Image Analysis with Applications in Public Safety.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Context Based Tattoo Image Analysis with Applications in Public Safety./
作者:	Kim, Joonsoo.
面頁冊數:	1 online resource (176 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
標題:	Electrical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9780355257557

Context Based Tattoo Image Analysis with Applications in Public Safety.
Kim, Joonsoo.

Context Based Tattoo Image Analysis with Applications in Public Safety. - 1 online resource (176 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related activities. In this thesis we examine several aspects of tattoo image analysis and how to extract useful information from tattoo images. There are problems with existing tattoo image systems. For example, many existing tattoo retrieval systems do not use local and global image descriptors robust to deformations caused by "manually constructed" tattoos on human skin. One other issue is that most tattoo images are manually cropped to remove background clutter from the image before analysis.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355257557Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Context Based Tattoo Image Analysis with Applications in Public Safety.
LDR:03447ntm a2200385Ki 4500 001 910503
005 20180517123956.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355257557
035 $a (MiAaPQ)AAI10601706
035 $a (MiAaPQ)purdue:21602
035 $a AAI10601706
040 $a MiAaPQ $b eng $c MiAaPQ
099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Kim, Joonsoo. $3 1181829
245 1 0 $a Context Based Tattoo Image Analysis with Applications in Public Safety.
264 0 $c 2017
300 $a 1 online resource (176 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
500 $a Adviser: Edward J. Delp.
502 $a Thesis (Ph.D.) $c Purdue University $d 2017.
504 $a Includes bibliographical references
520 $a Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related activities. In this thesis we examine several aspects of tattoo image analysis and how to extract useful information from tattoo images. There are problems with existing tattoo image systems. For example, many existing tattoo retrieval systems do not use local and global image descriptors robust to deformations caused by "manually constructed" tattoos on human skin. One other issue is that most tattoo images are manually cropped to remove background clutter from the image before analysis.
520 $a In this thesis we examined various aspects of a tattoo image retrieval and classification, in particular we investigated segmentation, classification, image matching and retrieval. A tattoo region is segmented using graph-cut tattoo segmentation based on image edges, a skin color model and a visual saliency map. We generate local and global image descriptors for the segmented image based on multiple polar histograms to introduce robustness against various deformations. The multiple polar histograms are combined with SIFT descriptors in the local image descriptor and 2D DFT in the global image descriptor. We then search our tattoo image database and retrieve images similar to the segmented image using an image matching technique based on both descriptors. To improve the image retrieval accuracy, not only we find the pairwise image similarity between an input image and a database image but we also incorporate all the image similarities between the database image and other database images using inductive matching.
520 $a For the tattoo image classification, sparse codes based on dense SIFT descriptors are generated. The sparse codes are then combined with a spatial pyramid feature pooling to incorporate the spatial distribution of the sparse codes. A spatial pyramid alignment method is additionally used to improve the image classification accuracy. These methods are evaluated on datasets that were collected from the Indiana State Police, eviltattoo.com, and the NIST tattoo challenge dataset.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
650 4 $a Computer engineering. $3 569006
650 4 $a Criminology. $3 563146
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
690 $a 0464
690 $a 0627
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Purdue University. $b Electrical and Computer Engineering. $3 1148521
773 0 $t Dissertation Abstracts International $g 79-03B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10601706 $z click for full text (PQDT)