Publication: Palm’s lines detection and automatic palmistry prediction system
dc.contributor.author | Tanasanee Phienthrakul | en_US |
dc.contributor.other | Mahidol University | en_US |
dc.date.accessioned | 2019-08-23T10:58:34Z | |
dc.date.available | 2019-08-23T10:58:34Z | |
dc.date.issued | 2018-01-01 | en_US |
dc.description.abstract | © Springer International Publishing AG 2018. This paper presents a method for palm and palm’s lines detection based on image processing techniques. An application of the proposed method is illustrated in the automatic palmistry system. Both hardware and software are created and tested. The system can detect palm and three main lines, i.e., life line, heart line, and brain line. Line’s position, line’s length, and line’s curvature are used for palmistry prediction. These three lines will be compared to the lines in the line pattern archives by using the nearest neighbor method. The experimental results show that this system can detect palm and palm’s lines and this system yields the suitable results on many examples. Furthermore, the concept of this system can be applied to identification and authentication in security approaches or in the embedded system fields. | en_US |
dc.identifier.citation | Advances in Intelligent Systems and Computing. Vol.684, (2018), 208-222 | en_US |
dc.identifier.doi | 10.1007/978-3-319-70016-8_18 | en_US |
dc.identifier.issn | 21945357 | en_US |
dc.identifier.other | 2-s2.0-85044435327 | en_US |
dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/45667 | |
dc.rights | Mahidol University | en_US |
dc.rights.holder | SCOPUS | en_US |
dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85044435327&origin=inward | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | Palm’s lines detection and automatic palmistry prediction system | en_US |
dc.type | Conference Paper | en_US |
dspace.entity.type | Publication | |
mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85044435327&origin=inward | en_US |