With the development of sensing technology, a large number of partial discharge (PD) time domain data are generated in the field of gas-insulated integrated electrical appliances (GIS). Traditional patternrecognition...
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data security and privacy are essential for transmitting, storing, and preserving medical images. This article provides a secure chaotic framework for medical imageencryption. The suggested technique has two stages: ...
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Reversible data concealment is a strategy that quietly alters digital material to keep secret data while allowing the original digital media to be totally restored without any error after extracting the concealed info...
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Point cloud registration is still a challenging and open problem. For example, when the overlap between two point clouds is extremely low, geo-only features may be not suf-ficient. Therefore, it is important to furthe...
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ISBN:
(数字)9798350353006
ISBN:
(纸本)9798350353013
Point cloud registration is still a challenging and open problem. For example, when the overlap between two point clouds is extremely low, geo-only features may be not suf-ficient. Therefore, it is important to further explore how to utilize color data in this task. Under such circumstances, we propose ColorPCR for color point cloud registration with multi-stage geometric-color fusion. We design a Hier-archical Color Enhanced Feature Extraction module to ex-tract multi-level geometric-color features, and a GeoColor Superpoint Matching Module to encode transformation-invariant geo-color global context for robust patch corre-spondences. In this way, both geometric and color data can be used, thus leading to robust performance even under extremely challenging scenarios, such as low overlap between two point clouds. To evaluate the performance of our method, we colorize 3DMatch/3DLoMatch datasets as Color3DMatch/Color3DLoMatch and evaluations on these datasets demonstrate the effectiveness of our proposed method. Our method achieves state-of-the-art registration recall of 97.5%/88.9% on them.
Non-Negative Matrix Factorization (NMF) has become a commonly used method for data representation. Orthogonal NMF improves the clustering performance by adding orthogonal constraints to the decomposed matrices. The ex...
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Content based video search services find extensive applications across various domains including video surveillance and object detection. In recent times, researchers have increasingly turned their attention towards e...
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Side match vector quantization (SMVQ) is a widely used image compression algorithm for data hiding applications. Compared with conventional vector quantization (VQ) algorithm, a smaller and more powerful state codeboo...
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Side match vector quantization (SMVQ) is a widely used image compression algorithm for data hiding applications. Compared with conventional vector quantization (VQ) algorithm, a smaller and more powerful state codebook (SC) which is generated by utilizing the correlation in natural image is used in SMVQ to achieve low bit rate. However, the visual quality of reconstructed image by using SMVQ is significantly decreased. In this paper, a novel low bit rate coding algorithm named structured SMVQ (SSMVQ) is proposed. The size of SSMVQ's SC is flexible and the SC of SSMVQ is composed by a smaller SC of conventional SMVQ and a supporting codebook which is newly introduced in this paper. Experimental results show that the proposed structed SMVQ is able to achieve satisfactory PSNR when the bit rate is extremely low.
Search order coding (SOC) benefits a lot from the correlation of neighboring blocks for vector quantization (VQ)-compressed images. SOC selects a number of different indices in its search path as candidate search orde...
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Search order coding (SOC) benefits a lot from the correlation of neighboring blocks for vector quantization (VQ)-compressed images. SOC selects a number of different indices in its search path as candidate search order codes. In this work, we present a low bit-rate SOC-based reversible data hiding algorithm benefiting from novel encoding strategies which exploit the information of the placeholders. The blocks are classified into two categories by the placeholders, where different encoding strategies are designed, respectively. Firstly, for the block in smooth region, the placeholders in its neighborhood are employed to compress the VQ index. Secondly, for the block in complex region, SOC is employed to compress the VQ index. Finally, for the blocks that cannot be processed by its placeholders and SOC, an effective prediction method named accurate gradient selective prediction (AGSP) and Huffman coding are introduced. After encoding phase, the size of the output bit stream is reduced so that space is saved for data embedding. Experiment results show that our proposed method outperforms other state-of-the-art SOC-based algorithms in bit rate and embedding capacity.
Side match vector quantization (SMVQ) algorithm is an effective low bit rate image compression algorithm which is very useful for data hiding techniques. By replacing the main codebook used in conventional vector quan...
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The proceedings contain 56 papers. The special focus in this conference is on Emerging Research in Computing, Information, Communication and applications. The topics include: IoT-Enabled Medicine Bottle;revamp Percept...
ISBN:
(纸本)9789811359521
The proceedings contain 56 papers. The special focus in this conference is on Emerging Research in Computing, Information, Communication and applications. The topics include: IoT-Enabled Medicine Bottle;revamp Perception of Bitcoin Using Cognizant Merkle;A Novel Algorithm for DNA Sequence compression;digiPen: An Intelligent Pen Using Accelerometer for Character recognition;Design of FPGA-Based Radar and Beam Controller;effect of Lattice Topologies and Distance Measurements in Self-Organizing Map for Better Classification;evaluation and Classification of Road Accidents Using Machine Learning Techniques;Multi-language Handwritten recognition in DWT Accuracy Analysis;a Novel H-∞ Filter Based Indicator for Health Monitoring of Components in a Smart Grid;developing Ontology for Smart Irrigation of Vineyards;a Survey on Intelligent Transportation System Using Internet of Things;CRUST: A C/C++ to Rust Transpiler Using a “Nano-parser Methodology” to Avoid C/C++ Safety Issues in Legacy Code;species Environmental Niche Distribution Modeling for Panthera Tigris Tigris ‘Royal Bengal Tiger’ Using Machine Learning;organizational Digital Footprint for Traceability, Provenance Approach;bidirectional Long Short-Term Memory for Automatic English to Kannada Back-Transliteration;a Dominant Point-Based Algorithm for Finding Multiple Longest Common Subsequences in Comparative Genomics;fast and Accurate Fingerprint recognition in Principal Component Subspace;smart Meter Analysis Using Big data Techniques;movie Recommendation System;a Semiautomated Question Paper Builder Using Long Short-Term Memory Neural Networks;an Intensive Review of data Replication Algorithms for Cloud Systems;time-Critical Transmission Protocols in Wireless Sensor Networks: A Survey;impact of Shuffler Design pattern on Software Quality;privacy-Preserving Lightweight imageencryption in Mobile Cloud;cyclic Scheduling Algorithm.
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