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020 _a9783319960029
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024 7 _a10.1007/978-3-319-96002-9
_2doi
050 4 _aTK5102.9
072 7 _aTJF
_2bicssc
072 7 _aUYS
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072 7 _aTEC008000
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072 7 _aUYS
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082 0 4 _a621.382
_223
245 1 0 _aNature Inspired Optimization Techniques for Image Processing Applications
_h[electronic resource] /
_cedited by Jude Hemanth, Valentina Emilia Balas.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXIV, 297 p. 130 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v150
505 0 _aFirefly Optimization Based Improved Fuzzy Clustering for CT/MR Image Segmentation -- Bat Optimization based Vector Quantization Algorithm for Medical Image Compression -- An Assertive Framework for Automatic Tamil Sign Language Recognition System using Computational Intelligence -- Improved detection of steganographic algorithms in spatial LSB stego images using hybrid GRASP-BGWO optimisation -- Nature inspired optimization techniques for Image Processing - A short review -- Application of Ant Colony Optimization for Enhancement of Visual Cryptography Images -- Plant phenotyping through Image analysis using nature inspired optimization techniques -- Cuckoo Optimization Algorithm (COA) for image processing -- Artificial Bee Colony Based Feature Selection for Automatic Skin Disease Identification of Mango Fruit -- Analyzing the Effect of Optimization Strategies in Deep Convolutional Neural Network -- A Novel Underwater Image Enhancement Approach with Wavelet Transform Supported by Differential Evolution Algorithm -- Feature Selection in Fetal Biometrics for Abnormality Detection in Ultrasound Images.
520 _aThis book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications.
650 0 _aSignal processing.
_94052
650 0 _aImage processing—Digital techniques.
_931565
650 0 _aComputer vision.
_937662
650 0 _aMathematical optimization.
_94112
650 1 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aOptimization.
_937663
700 1 _aHemanth, Jude.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_937664
700 1 _aBalas, Valentina Emilia.
_eeditor.
_0(orcid)0000-0003-0885-1283
_1https://orcid.org/0000-0003-0885-1283
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_937665
710 2 _aSpringerLink (Online service)
_937666
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319960012
776 0 8 _iPrinted edition:
_z9783319960036
776 0 8 _iPrinted edition:
_z9783030071264
830 0 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v150
_937667
856 4 0 _uhttps://doi.org/10.1007/978-3-319-96002-9
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c76214
_d76214