Segmentation of CAPTCHA Using Corner Detection and Clustering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246213" target="_blank" >RIV/61989100:27240/20:10246213 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-50097-9_67" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-50097-9_67</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-50097-9_67" target="_blank" >10.1007/978-3-030-50097-9_67</a>
Alternative languages
Result language
angličtina
Original language name
Segmentation of CAPTCHA Using Corner Detection and Clustering
Original language description
Character segmentation is the key to CAPTCHA recognition. In order to solve the problem of low success rate of CAPTCHA segmentation caused by adhesive characters, an adhesion character segmentation algorithm based on corner detection and K-Means clustering was proposed. The algorithm performs corner detection on the CAPTCHA image of the adhesive characters, then uses K-Means clustering method to cluster the corner points of ROI, and determines the adhesion character segmentation line from the clustering results. The experimental results are compared with the drop-fall and skeletonization, in which the recognition accuracy of the image with serious adhesion is 92%. The result shows the superiority of the segmentation algorithm and provides a new method for the segmentation of adhesive characters.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 1156
ISBN
978-3-030-50096-2
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
12
Pages from-to
655-666
Publisher name
Springer
Place of publication
Cham
Event location
Ostrava
Event date
Dec 2, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000590145400067