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...
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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 patternrecognitionencryption techniques.
Volume xi of the Transactions on Rough Sets (TRS) provides evidence of f- ther growth in the rough set landscape, both in terms of its foundations and applications. This volume provides further evidence of the number ...
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ISBN:
(数字)9783642114793
ISBN:
(纸本)9783642114786
Volume xi of the Transactions on Rough Sets (TRS) provides evidence of f- ther growth in the rough set landscape, both in terms of its foundations and applications. This volume provides further evidence of the number of research streams that were either directly or indirectly initiated by the seminal work on rough 1 sets by Zdzis law Pawlak (1926-2006) . Evidence of the growth of various rough 2 set-based research streams can be found in the rough set database . Thisvolumecontainsarticlesintroducingadvancesinthefoundationsand- *** advancesinclude: calculusofattribute-value pairs useful in mining numerical data, de?nability and coalescence of approximations, variable consistency generalization approach to bagging controlled by measures of consistency, classical and dominance-based rough sets in the search for genes, judgementaboutsatis?abilityunderincompleteinformation,irreducibledescr- tive sets of attributes for information systems useful in the design of concurrent data models, computational theory of perceptions (CTP) and its characteristics and the relation with fuzzy-granulation, methods and algorithms of the Net- TRS system, a recursive version of the apriori algorithm designed for parallel processing, and decision table reduction method based on fuzzy rough sets. Theeditorsandauthorsofthisvolumeextendtheirgratitudetothereviewers of articles in this volume, Alfred Hofmann, Ursula Barth, Christine Reiss and the LNCS sta? at Springer for their support in making this volume of the TRS possible.
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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