| 000 | 04868nam a22005535i 4500 | ||
|---|---|---|---|
| 001 | 978-3-030-44613-0 | ||
| 003 | DE-He213 | ||
| 005 | 20240423125006.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 200422s2020 sz | s |||| 0|eng d | ||
| 020 |
_a9783030446130 _9978-3-030-44613-0 |
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| 024 | 7 |
_a10.1007/978-3-030-44613-0 _2doi |
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| 050 | 4 | _aTA1634 | |
| 072 | 7 |
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| 082 | 0 | 4 |
_a006.37 _223 |
| 100 | 1 |
_aDi Martino, Ferdinando. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 245 | 1 | 0 |
_aFuzzy Transforms for Image Processing and Data Analysis _h[electronic resource] : _bCore Concepts, Processes and Applications / _cby Ferdinando Di Martino, Salvatore Sessa. |
| 250 | _a1st ed. 2020. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
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| 300 |
_aX, 217 p. 155 illus., 71 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 505 | 0 | _a1. Fuzzy Transform Concepts -- 2. Multi-dimensional High Degree Fuzzy Transform -- 3. Fuzzy Transform for Image and Video Compression -- 4. Fuzzy Transform Technique for Image Auto Focus -- 5. Fuzzy Transform for Image Fusion and Edge Detection. | |
| 520 | _aThis book analyzes techniques that use the direct and inverse fuzzy transform for image processing and data analysis. The book is divided into two parts, the first of which describes methods and techniques that use the bi-dimensional fuzzy transform method in image analysis. In turn, the second describes approaches that use the multidimensional fuzzy transform method in data analysis. An F-transform in one variable is defined as an operator which transforms a continuous function f on the real interval [a,b] in an n-dimensional vector by using n-assigned fuzzy sets A1, … , An which constitute a fuzzy partition of [a,b]. Then, an inverse F-transform is defined in order to convert the n-dimensional vector output in a continuous function that equals f up to an arbitrary quantity ε. We may limit this concept to the finite case by defining the discrete F-transform of a function f in one variable, even if it is not known a priori. A simple extension of this concept to functions in two variables allows it to be used for the coding/decoding and processing of images. Moreover, an extended version with multidimensional functions can be used to address a host of topics in data analysis, including the analysis of large and very large datasets. Over the past decade, many researchers have proposed applications of fuzzy transform techniques for various image processing topics, such as image coding/decoding, image reduction, image segmentation, image watermarking and image fusion; and for such data analysis problems as regression analysis, classification, association rule extraction, time series analysis, forecasting, and spatial data analysis. The robustness, ease of use, and low computational complexity of fuzzy transforms make them a powerful fuzzy approximation tool suitable for many computer science applications. This book presents methods and techniques based on the use of fuzzy transforms in various applications of image processing and data analysis, including image segmentation, image tamper detection, forecasting, and classification, highlighting the benefits they offer compared with traditional methods. Emphasis is placed on applications of fuzzy transforms to innovative problems, such as massive data mining, and image and video security in social networks based on the application of advanced fragile watermarking systems. This book is aimed at researchers, students, computer scientists and IT developers to acquire the knowledge and skills necessary to apply and implement fuzzy transforms-based techniques in image and data analysis applications. | ||
| 650 | 0 | _aComputer vision. | |
| 650 | 0 | _aData mining. | |
| 650 | 0 |
_aComputer science _xMathematics. |
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| 650 | 0 | _aArtificial intelligence. | |
| 650 | 1 | 4 | _aComputer Vision. |
| 650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
| 650 | 2 | 4 | _aMathematical Applications in Computer Science. |
| 650 | 2 | 4 | _aArtificial Intelligence. |
| 700 | 1 |
_aSessa, Salvatore. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030446123 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030446147 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030446154 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-44613-0 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 942 | _cSPRINGER | ||
| 999 |
_c173009 _d173009 |
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