Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/394938
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dc.contributor.authorWing Teng Ho-
dc.contributor.authorYong Haur Tay-
dc.date.accessioned2023-06-15T07:52:29Z-
dc.date.available2023-06-15T07:52:29Z-
dc.identifier.otherukmvital:122432-
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/394938-
dc.description.abstractAdaBoost has been verified to be proficient in processing images rapidly while attaining high detection rate in face detection. The speed of AdaBoost in face detection is demonstrated in [1], where the detection can be performed in 15 frames per second. The robust speediness and the high accuracy in tracing the target objects have enable AdaBoost to be successful in classification problems. In this paper, we examine the capability of Adaboost with Haar-like features in detecting text in image. We distinguish text into two categories, i.e. fixed text and variable text, which represent spatially similar and dissimilar objects, respectively. As a reference, we first present a face detector using AdaBoost with Haar-like feature. Next, we apply the same feature set on fixed text detection and variable texts detection. Experimental results show that Haar-like features in AdaBoost is suitable for detecting spatially similar objects such as faces and fixed texts. However, these features are not adequate in detecting spatially dissimilar objects such as variable text.-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE),Piscataway, US-
dc.subjectAdaboost-
dc.subjectFace detection-
dc.titleOn detecting spatially similar and dissimilar objects using Adaboost-
dc.typeSeminar Papers-
dc.format.pages5-
dc.identifier.callnoT58.5.C634 2008 kat sem j.2-
dc.contributor.conferencenameInternational Symposium on Information Technology-
dc.coverage.conferencelocationKuala Lumpur Convention Centre-
dc.date.conferencedate26/08/2008-
Appears in Collections:Seminar Papers/ Proceedings / Kertas Kerja Seminar/ Prosiding

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