Fuzzy Transforms for Image Processing and Data Analysis (Record no. 173009)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04868nam a22005535i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-44613-0 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240423125006.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200422s2020 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783030446130 |
| -- | 978-3-030-44613-0 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-030-44613-0 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA1634 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQV |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM016000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQV |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.37 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Di Martino, Ferdinando. |
| Relator term | author. |
| Relator code | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 245 10 - TITLE STATEMENT | |
| Title | Fuzzy Transforms for Image Processing and Data Analysis |
| Medium | [electronic resource] : |
| Remainder of title | Core Concepts, Processes and Applications / |
| Statement of responsibility, etc | by Ferdinando Di Martino, Salvatore Sessa. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2020. |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | X, 217 p. 155 illus., 71 illus. in color. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 1. 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 ## - SUMMARY, ETC. | |
| Summary, etc | This 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 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer vision. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science |
| General subdivision | Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Vision. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematical Applications in Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Sessa, Salvatore. |
| Relator term | author. |
| Relator code | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783030446123 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783030446147 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783030446154 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-030-44613-0">https://doi.org/10.1007/978-3-030-44613-0</a> |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-CSE-Springer |
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