Search results for "Blossom algorithm"
showing 6 items of 6 documents
MoMo: enabling hybrid museums
2005
Present-day museums are not mere passive institutions for the preservation of a society's cultural heritage. They have become instead learning environments, research centres and even tourist attractions. The paper introduces the notion of a hybrid museum (HM) in which wireless personal digital devices (PDAs) are used to tailor digital contents to the visitor to enrich both the learning and entertainment experience. The paper describes a fully functional hybrid museum infrastructure (MoMo) implemented with the.NET compact framework running on the PocketPC platform. Several research challenges that had to be faced during the implementation of the system such as the exploration of large sets o…
Secure and Privacy Preserving Pattern Matching in Distributed Cloud-based Data Storage
2019
Given two strings: pattern $p$ of length $m$ and text $t$ of length $n$ . The string matching problem is to find all (or some) occurrences of the pattern $p$ in the text $t$ . We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.
Fingerprint Registration Using Specialized Genetic Algorithms
2005
One of the most common problem to realize a robust matching algorithm in an Automated Fingerprint Identification System (AFIS) is the images registration. In this paper a fingerprints registration method based on a specialized genetic algorithm (GA) is proposed. A global transformation between two fingerprint images is performed using genetic data evolutions based on specialized mutation rate and solution refining. An AFIS including the above method has been developed and tested on two different fingerprint databases: NIST 4 ink-on-paper and self optical scanned. The obtained experimental results show that the proposed approach is comparable with literature systems working on medium quality…
Social Network-Based Content Delivery in Device-to-Device Underlay Cellular Networks Using Matching Theory
2017
With the popularity of social network-based services, the unprecedented growth of mobile date traffic has brought a heavy burden on the traditional cellular networks. Device-to-device (D2D) communication, as a promising solution to overcome wireless spectrum crisis, can enable fast content delivery based on user activities in social networks. In this paper, we address the content delivery problem related to optimization of peer discovery and resource allocation by combining both the social and physical layer information in D2D underlay networks. The social relationship, which is modeled as the probability of selecting similar contents and estimated by using the Bayesian nonparametric models…
Performance evaluation of simple fingerprint minutiae extraction algorithm using crossing number on valley structure
2008
In fingerprint recognition system, performance of fingerprint feature extraction algorithm is important. We use visual analysis to evaluate this performance. 100 respondents fill a questionnaire consisting of 30 images from fingerprint feature extraction process. We get 12,3 % minutiae points missed by this algorithm. With BOZORTH3 minutiae matching algorithm, the distribution of matching score of 80-fingerprint images are presented and we obtain EER 5.89 % at threshold value 180.
Introducing Pseudo-Singularity Points for Efficient Fingerprints Classification and Recognition
2010
Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Generally, fingerprint recognition is based on a set of relevant local characteristics, such as ridge ending and bifurcation (minutiae). Fingerprint classification is based on fingerprint global features, such as core and delta singularity points. Unfortunately, singularity points are not always present in a fingerprint image: the acquisition process is not ideal, so that the fingerprint is broken, or the fingerprint belongs to the arch class. In the above cases, pseudo-singularity-points will be detected and extracted to make possible fingerprint classification and matching. As result, fingerpr…