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A Novel Infrared Touch Sensing Using K-Nearest Neighbor Algorithm

A Novel Infrared Touch Sensing Using K-Nearest Neighbor Algo...

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3rd international conference on Computer and Knowledge Engineering (ICCKE)

作者： Jafarizadeh, Saeid Boostani, Reza Safavi, Ali Akbar Shiraz Univ Elect & Comp Engn Sch Vis Lab Shiraz Iran

ISBN: (纸本)9781479920938

Production and usage of touch sensing has attracted much attention, nevertheless, the current touch screen systems highly suffer from the dependency on the platform material. To overcome this drawback, here, a novel method is proposed by considering the infrared transmitters and receivers sensors instead of the piezoelectric sensors. In this way, the transformed platform works based on employing K-nearest neighbor (KNN) in conjunction with the spatial-temporal windowing to increase the sensitivity and accuracy of the detecting the finger place on the screen. To verify the proposed approach, the necessary hardware was set up. To test the hardware, the platform is locally segmented (e. g. like a grid) into a 7*8 table and 50 persons with different finger size were participated. Experimental results show the superior efficiency of the proposed method compare to the conventional methods.

关键词： Touch sensing K-nearest neighbor (KNN) algorithm Infrared sensors pattern recognition piezoelectric sensors

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Local morphological pattern spectrum based approach for off-line signature verification

Local morphological pattern spectrum based approach for off-...

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5th international conference on pattern recognition and Machine Intelligence, PReMI 2013

作者： Shekar, B.H. Bharathi, R.K. Pilar, Bharathi Department of Computer Science Mangalore University Karnataka India Department of Master of Computer Applications S J College of Engineering Mysore Karnataka India Department of Master of Computer Applications AIMIT St. Aloysius College Mangalore Karnataka India

ISBN: (纸本)9783642450617

In this paper, we present a local morphological pattern spectrum based approach for off-line signature verification. The proposed approach has three major phases : Preprocessing, Feature extraction and Classification. In the feature extraction phase, the signature image is partitioned into eight equally sized vertical blocks and local morphological pattern spectra of each block is obtained. The spectrum thus obtained for each block is converted to normalised ten bin histogram and to form a feature vector of the signature. The Earth Movers Distance (EMD) measure is used for classification and the performance is measured through FAR/FRR metric. Experiments have been conducted on standard signature datasets namely CEDAR and GPDS-160, and MUKOS, a regional language (Kannada) dataset. The comparative study is also provided with the well known approaches to exhibit the performance of the proposed approach. © Springer-Verlag 2013.

关键词： Feature extraction

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A fast agglomerative community detection method for protein complex discovery in protein interaction networks

A fast agglomerative community detection method for protein ...

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8th iapr international conference on pattern recognition in bioinformatics, PRIB 2013

作者： Rahman, Mohammad S. Ngom, Alioune School of Computer Sciences University of Windsor 5115 Lambton Tower Windsor ON N9B 3P4 Canada

ISBN: (纸本)9783642391583

Proteins are known to interact with each other by forming protein complexes and in order to perform specific biological functions. Many community detection methods have been devised for the discovery of protein complexes in protein interaction networks. One common problem in current agglomerative community detection approaches is that vertices with just one neighbor are often classified as separate clusters, which does not make sense for complex identification. Also, a major limitation of agglomerative techniques is that their computational efficiency do not scale well to large protein interaction networks (PINs). In this paper, we propose a new agglomerative algorithm, FAC-PIN, based on a local premetric of relative vertex-to-vertex clustering value and which addresses the above two issues. Our proposed FAC-PIN method is applied to eight PINs from different species, and the identified complexes are validated using experimentally verified complexes. The preliminary computational results show that FAC-PIN can discover protein complexes from PINs more accurately and faster than the HC-PIN and CNM algorithms, the current state-of-the-art agglomerative approaches to complex prediction. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Computational efficiency

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A Novel Illumination Normalization Algorithm for Face recognition

A Novel Illumination Normalization Algorithm for Face Recogn...

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3rd IEEE international conference on Signal and Image Processing Applications (ICSIPA)

作者： Bashier, Housam Khalifa Hoe, Lau Siong Han, Pang Ying Ping, Liew Yee Multimedia Univ Fac Informat Sci & Technol Lalan Ayer Keroh Lama 75450 Melaka Malaysia

ISBN: (纸本)9781479902699;9781479902675

face recognitions systems suffer from the problem associated with illumination variation. Therefore, there's a need to address this problem. In this paper, we present a novel algorithm for illumination normalization call Local Trapezoid Feature LTF. The features are derived from the trapezoid rule and the experiments results on extended Yale face database demonstrated the effectiveness and the superiority of the algorithm. Furthermore, our algorithm doesn't require dimensionality reduction or feature extraction.

关键词： Local Trapezoid Feature image processing pattern recognition Illumination variation face recognition

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ALP: An Authentication and Leak Prediction Model for Cloud Computing Privacy

ALP: An Authentication and Leak Prediction Model for Cloud C...

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3rd IEEE international Advance Computing conference (IACC)

作者： Farhatullah, Mohammad Dr L Bullayya Coll Engn Women Dept CSE Visakhapatnam Andhra Pradesh India

ISBN: (纸本)9781467345286

The current paper is an attempt to integrate privacy preservation with privacy leak detection in the context of text mining. This may be considered as extending the Storage as a Service feature of Cloud Computing wherein the user in the role of content creator submits the documents to be stored. There exists a facility to cluster these documents based on the concept-based mining algorithm. The clustered documents are usually available in the form a tree. When a user in the role of a subscriber requests to access a document, this request for access will have to go through an authentication procedure based on the Leakage Free Redactable Signature Scheme. Access control information is being maintained in the form of a Cloud user access control list. A privacy detection leak module which detects privacy leaks depending upon the pattern of previous privacy leaks is also being proposed. This information is then used to update the cloud user access control list and users responsible for privacy leaks are prevented from accessing the cloud service. The current document being requested by the user together with the information from the access control list is used to decide which part of the redacted trees have to be made available to the user as a response. Thus this combination of this authentication procedure and privacy leak detection can be used to ensure the privacy of the sensitive information stored by the user in the cloud.

关键词： Cloud Computing Privacy Authentication pattern recognition

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Anomaly Detection Using Motion patterns Computed From Optical Flow

Anomaly Detection Using Motion Patterns Computed From Optica...

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3rd international conference on Advances in Computing and Communications (ICACC)

作者： Parvathy, R. Thilakan, Soumya Joy, Meenu Sameera, K. M. ASIET Ernakulam Kerala India

ISBN: (纸本)9780769550336

A method is proposed for detecting anomalies in extremely crowded scenes using analysis of motion patterns. The optical flow is computed by initializing the video as a dynamical system. Optical flow is a vector field where each vector represents the direction and amount of motion. This generated model can be used to define trajectories. Then these trajectories are clustered hierarchically using spatial and temporal information for learning the motion patterns. Based on the learned statistical motion patterns, anomalies are detected using statistical methods.

关键词： Optical Flow Trajectories pattern recognition

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Local topological signatures for network-based prediction of biological function

Local topological signatures for network-based prediction of...

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8th iapr international conference on pattern recognition in bioinformatics, PRIB 2013

作者： Winterbach, Wynand Van Mieghem, Piet Reinders, Marcel J. T. Wang, Huijuan De Ridder, Dick Network Architectures and Services Group Delft University of Technology P.O. Box 5031 2600 GA Delft Netherlands Department of Intelligent Systems Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology P.O. Box 5031 2600 GA Delft Netherlands Netherlands Bioinformatics Center 6500 HB Nijmegen Netherlands Kluyver Centre for Genomics of Industrial Fermentation 2600 GA Delft Netherlands

ISBN: (纸本)9783642391583

In biology, similarity in structure or sequence between molecules is often used as evidence of functional similarity. In protein interaction networks, structural similarity of nodes (i.e., proteins) is often captured by comparing node signatures (vectors of topological properties of neighborhoods surrounding the nodes). In this paper, we ask how well such topological signatures predict protein function, using protein interaction networks of the organism Saccharomyces cerevisiae. To this end, we compare two node signatures from the literature - the graphlet degree vector and a signature based on the graph spectrum - and our own simple node signature based on basic topological properties. We find the connection between topology and protein function to be weak but statistically significant. Surprisingly, our node signature, despite its simplicity, performs on par with the other more sophisticated node signatures. In fact, we show that just two metrics, the link count and transitivity, are enough to classify protein function at a level on par with the other signatures suggesting that detailed topological characteristics are unlikely to aid in protein function prediction based on protein interaction networks. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Yeast

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The research of label identification method based on fuzzy theory

The research of label identification method based on fuzzy t...

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3rd international conference on Materials Science and Information Technology, MSIT 2013

作者： Bu, Xiao Yu Liu, Ping Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9783037857700

This paper is mainly discussing the key technology of label automatic identification system using the indirect fuzzy pattern recognition based on the features of image and the fuzzy theory. This method greatly improves the efficiency and accuracy and the control effect is obvious, so that the quality of the label is guaranteed. © (2013) Trans Tech Publications, Switzerland.

关键词： pattern recognition

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A novel Algorithm for Image Compression and pattern Matching

A novel Algorithm for Image Compression and Pattern Matching

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3rd international conference on Advances in Computing and Communications (ICACC)

作者： Shamna, P. Tripti, C. Augustine, Paul Rajagiri Sch Engn & Technol Dept Comp Sci Kochi 39 Kerala India

ISBN: (纸本)9780769550336

The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. Compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for pattern recognition encryption techniques.

关键词： Image Processing Image Compression pattern Matching Encryption

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Comprehensive Evaluation on Exploitation and Utilization of Water Resources Based on Improved Fuzzy pattern recognition Model

Comprehensive Evaluation on Exploitation and Utilization of ...

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3rd international conference on Civil Engineering, Architecture and Building Materials (CEABM 2013)

作者： Chen, Huawei Fan, Mingyuan Huang, Jiwen Zhang, Xin Liu, Haijiao Fu, Shidong Water Res Inst Shandong Prov Jinan 250013 Peoples R China

ISBN: (纸本)9783037857779

Through identifying the exploitation and utilization of water resources system, this paper establishes an improved fuzzy pattern recognition model by combining fuzzy matter-element model with the improved entropy evaluation method and sets up the comprehensive evaluation index system which includes 3 layers and 10 indicators from two aspects: water utilization efficiency and water ecological environment. The proposed model and evaluation index system are applied to evaluate the comprehensive exploitation-utilization grade in Shandong Province. Results show that the exploitation-utilization of water resources and water ecological environment are not balanced in Shandong province, this indicates that the growth of ecological benefits and the protection of water ecological environment are ignored in the process of water resources exploitation-utilization.

关键词： exploitation and utilization of water resources comprehensive evaluation index system the improved fuzzy pattern recognition model Shandong province

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