Incorporates functions for image preprocessing, filtering and image recognition. The package takes advantage of 'RcppArmadillo' to speed up computationally intensive functions. The histogram of oriented gradients descriptor is a modification of the 'findHOGFeatures' function of the 'SimpleCV' computer vision platform, the average_hash(), dhash() and phash() functions are based on the 'ImageHash' python library. The Gabor Feature Extraction functions are based on 'Matlab' code of the paper, "CloudID: Trustworthy cloud-based and cross-enterprise biometric identification" by M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, Expert Systems with Applications, vol. 42, no. 21, pp. 7905-7916, 2015, <doi:10.1016/j.eswa.2015.06.025>. The 'SLIC' and 'SLICO' superpixel algorithms were explained in detail in (i) "SLIC Superpixels Compared to State-of-the-art Superpixel Methods", Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, num. 11, p. 2274-2282, May 2012, <doi:10.1109/TPAMI.2012.120> and (ii) "SLIC Superpixels", Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, EPFL Technical Report no. 149300, June 2010.
| Version: | 1.1.7 |
| Depends: | R (≥ 3.2.3) |
| Imports: | Rcpp (≥ 0.12.17), graphics, grid, shiny, jpeg, png, tiff, R6 |
| LinkingTo: | Rcpp, RcppArmadillo (≥ 0.8.0) |
| Suggests: | testthat, knitr, rmarkdown, covr |
| Published: | 2020-06-18 |
| Author: | Lampros Mouselimis [aut, cre], Sight Machine [cph] (findHOGFeatures function of the SimpleCV computer vision platform), Johannes Buchner [cph] (average_hash, dhash and phash functions of the ImageHash python library), Mohammad Haghighat [cph] (Gabor Feature Extraction), Radhakrishna Achanta [cph] (Author of the C++ code of the SLIC and SLICO algorithms (for commercial use please contact the author)) |
| Maintainer: | Lampros Mouselimis <mouselimislampros at gmail.com> |
| BugReports: | https://github.com/mlampros/OpenImageR/issues |
| License: | GPL-3 |
| Copyright: | inst/COPYRIGHTS OpenImageR copyright details |
| URL: | https://github.com/mlampros/OpenImageR |
| NeedsCompilation: | yes |
| SystemRequirements: | libarmadillo: apt-get install -y libarmadillo-dev (deb), libblas: apt-get install -y libblas-dev (deb), liblapack: apt-get install -y liblapack-dev (deb), libarpack++2: apt-get install -y libarpack++2-dev (deb), gfortran: apt-get install -y gfortran (deb), libjpeg-dev: apt-get install -y libjpeg-dev (deb), libpng-dev: apt-get install -y libpng-dev (deb), libfftw3-dev: apt-get install -y libfftw3-dev (deb), libtiff5-dev: apt-get install -y libtiff5-dev (deb) |
| Materials: | README NEWS |
| CRAN checks: | OpenImageR results |
| Reference manual: | OpenImageR.pdf |
| Vignettes: |
Gabor Feature extraction Image segmentation based on Superpixels and Clustering Functionality of the OpenImageR package |
| Package source: | OpenImageR_1.1.7.tar.gz |
| Windows binaries: | r-devel: OpenImageR_1.1.7.zip, r-release: OpenImageR_1.1.7.zip, r-oldrel: OpenImageR_1.1.7.zip |
| macOS binaries: | r-release: OpenImageR_1.1.7.tgz, r-oldrel: OpenImageR_1.1.7.tgz |
| Old sources: | OpenImageR archive |
| Reverse imports: | CNVScope, imagefluency, SuperpixelImageSegmentation |
| Reverse linking to: | SuperpixelImageSegmentation |
| Reverse suggests: | ClusterR |
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