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Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

2009

Computer Engineering

Retrieval

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Coherent Phrase Model For Efficient Image Near-Duplicate Retrieval, Yiqun Hu, Xiangang Cheng, Liang-Tien Chia, Xing Xie, Deepu Rajan, Ah-Hwee Tan Dec 2009

Coherent Phrase Model For Efficient Image Near-Duplicate Retrieval, Yiqun Hu, Xiangang Cheng, Liang-Tien Chia, Xing Xie, Deepu Rajan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents an efficient and effective solution for retrieving image near-duplicate (IND) from image database. We introduce the coherent phrase model which incorporates the coherency of local regions to reduce the quantization error of the bag-of-words (BoW) model. In this model, local regions are characterized by visual phrase of multiple descriptors instead of visual word of single descriptor. We propose two types of visual phrase to encode the coherency in feature and spatial domain, respectively. The proposed model reduces the number of false matches by using this coherency and generates sparse representations of images. Compared to other method, the …

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Correlating Orphaned Windows Registry Data Structures, Damir Kahvedžić, Tahar Kechadi Jan 2009

Correlating Orphaned Windows Registry Data Structures, Damir Kahvedžić, Tahar Kechadi

Journal of Digital Forensics, Security and Law

Recently, it has been shown that deleted entries of the Microsoft Windows registry (keys) may still reside in the system files once the entries have been deleted from the active database. Investigating the complete keys in context may be extremely important from both a Forensic Investigation point of view and a legal point of view where a lack of context can bring doubt to an argument. In this paper we formalise the registry behaviour and show how a retrieved value may not maintain a relation to the part of the registry it belonged to and hence lose that context. We …

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