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Sta­tistik mit Anwendungen im Be­reich der Ingenieur­wissen­schaften

Software-Pakete / Software Packages


R-package crackrec for crack recognition

This R package provides R functions for dectecting and plotting cracks in images. These functions were developed in the SFB/TR TRR 30 Project D6 and are described in more detail in:

  • Gunkel, C., Stepper, A., Müller, A. C., Müller, C. H. (2009). Micro crack detection with Dijkstra's shortest path algorithm. Submitted.

Für R 2.12.1:

1. crackrec_2.1.6.zip is a binary zip file of the Window version which can be called by "packages".

2. crackrec_2.1.6.tar.gz contains the files to install the package  under UNIX/LINUX by the command "R CMD INSTALL crackrec".

Für R 2.9.2:

1. crackrec_2.1.5.zip is a binary zip file of the Window version which can be called by "packages".

2. crackrec_2.1.5.tgz is the Mac binary.

3. crackrec_2.1.5_source.zip  contains the original files.

4. crackrec_2.1.5.tar.gz contains the files to install the package  under UNIX/LINUX by the command "R CMD INSTALL crackrec".

Image.bmp contains an example image as bmp file and example.txt provides examples of R commands to analyse the image with crackrec. The package crackrec includes a median filter. But a faster C program for the median was developed by Ryan Tibshirani.

 

 

R-package epsi for edge preserving smoothing in images

This R package provides R functions for smoothing noisy images so that edges are preserved. Some of them preserve also corners, some of them eliminate outliers, and some do both. These functions were developed in the DFG project Mu 1031/4-1/2 and are described in more detail in:

  • Chu, C. K., Glad, I. K., Godtliebsen, F., Marron, J. S. (1998). Edge-preserving smoothers for image processing. J. Amer. Statist. Assoc. 93, 526-541.
  • Müller, Ch.H. (2002). Robust estimators for estimating discontinuous functions. Metrika 55, 99-109.
  • Müller, Ch.H. (2002). Comparison of high-breakdown-point estimators for image denoising. Allg. Stat. Archiv 86, 307-321.
  • Hillebrand, M. and Ch.H. Müller (2006). On consistency of redescending M-kernel smoothers. Metrika 63, 71 - 90.
  • Hillebrand, M. and Ch.H. Müller ((2007). Outlier robust corner-preserving methods for reconstructing noisy images. Ann. Statist. 35, 132-165.

1. epsi.zip is an old zip file of the old Window version which could be called by "packages".

2. epsi_2009.zip is a new zip file of the new Window version which can be called by "packages".

3. epsi_1.0-1.tar.gz contains the original files and the package is installed under UNIX by the command "R CMD INSTALL epsi".

 

 

R-package edci for edge detection and clustering in images

This R package provides R functions for detection of pixel positions close to edges and for finding regression clusters within these pixel positions which provides the true edges. The package provides not only functions for detection of linear edges but also for detection of circles. These functions were developed in the DFG project Mu 1031/4-1/2 and are described in more detail in:

  • Qiu, P. (1997). Nonparametric estimation of jump surface. The Indian Journal of Statistics 59, Series A, 268-294.
  • Garlipp, T. and Müller, Ch. H. (2004). Regression Clustering with Redescending M-Estimators. In: Daniel Baier and Klaus-Dieter Wernecke (eds.): Innovations in Classification, Data Science, and Information Systems. Springer-Verlag, Heidelberg, 38-45.
  • Müller, Ch.H. and T. Garlipp (2005). Simple consistent cluster methods based on redescending M-estimators with an application to edge identification in images. Journal of Multivariate Analysis 92, 359-385.
  • Garlipp, T. and Müller, Ch.H. (2006). Detection of linear and circular shapes in image analysis. Computational Statistics and Data Analysis 51, 1479-1490.
  • Garlipp, T. and Müller, Ch.H. (2007). Robust jump detection in regression surface. Sankrya 69, 55-86.

1. edci.zip is an old zip file of the old Window version which could be called by "packages".

2. edci_2009.zip is a new zip file of the new Window version which can be called by "packages".

3. edci_1.0-1.tar.gz contains the old original files and the package is installed under UNIX by the command "R CMD INSTALL edci".

4. edci_1.0-1_2009.zip contains updated original files.

5. edci_1.1-1.tar.gz contains a new version from 2016.

 

 

R-package lsdepth for calculating the Student location-scale depth and the Student median

This R package provides R functions for calculating the Student location-scale depth and the Student median described in the paper "Mizera, I. and Ch.H. Müller (2003). Location-scale depth. Journal of American Statistical Association 99, 949-966.". These functions are based on Theorems 8 and 9 of this paper and do not use the transformation to the Klein disk. In particular, by using Theorem 9, an exact method for calculating the depth contours for continuous distributions is provided. Additionally, functions are included which provide the scale parameter with maximum depth for given location parameters.

1. lsdepth_R_win.zip is a zip file of the Window version which can be called by "packages".

2. lsdepth_R.zip contains the original files and the package is installed under UNIX by the command "R CMD INSTALL lsdepth".

 

 

Location & approach

The campus of TU Dort­mund University is located close to interstate junction Dort­mund West, where the Sauerlandlinie A 45 (Frankfurt-Dort­mund) crosses the Ruhrschnellweg B 1 / A 40. The best interstate exit to take from A 45 is “Dort­mund-Eichlinghofen” (closer to South Campus), and from B 1 / A 40 “Dort­mund-Dorstfeld” (closer to North Campus). Signs for the uni­ver­si­ty are located at both exits. Also, there is a new exit before you pass over the B 1-bridge leading into Dort­mund.

To get from North Campus to South Campus by car, there is the connection via Vogelpothsweg/Baroper Straße. We recommend you leave your car on one of the parking lots at North Campus and use the H-Bahn (suspended monorail system), which conveniently connects the two campuses.

TU Dort­mund University has its own train station (“Dort­mund Uni­ver­si­tät”). From there, suburban trains (S-Bahn) leave for Dort­mund main station (“Dort­mund Hauptbahnhof”) and Düsseldorf main station via the “Düsseldorf Airport Train Station” (take S-Bahn number 1, which leaves every 15 or 30 minutes). The uni­ver­si­ty is easily reached from Bochum, Essen, Mülheim an der Ruhr and Duisburg.

You can also take the bus or subway train from Dort­mund city to the uni­ver­si­ty: From Dort­mund main station, you can take any train bound for the Station “Stadtgarten”, usually lines U41, U45, U 47 and U49. At “Stadtgarten” you switch trains and get on line U42 towards “Hombruch”. Look out for the Station “An der Palmweide”. From the bus stop just across the road, busses bound for TU Dort­mund University leave every ten minutes (445, 447 and 462). Another option is to take the subway routes U41, U45, U47 and U49 from Dort­mund main station to the stop “Dort­mund Kampstraße”. From there, take U43 or U44 to the stop “Dort­mund Wittener Straße”. Switch to bus line 447 and get off at “Dort­mund Uni­ver­si­tät S”.

The AirportExpress is a fast and convenient means of transport from Dortmund Airport (DTM) to Dortmund Central Station, taking you there in little more than 20 minutes. From Dortmund Central Station, you can continue to the university campus by interurban railway (S-Bahn). A larger range of international flight connections is offered at Düsseldorf Airport (DUS), which is about 60 kilometres away and can be directly reached by S-Bahn from the university station.

The H-Bahn is one of the hallmarks of TU Dort­mund University. There are two stations on North Campus. One (“Dort­mund Uni­ver­si­tät S”) is directly located at the suburban train stop, which connects the uni­ver­si­ty directly with the city of Dort­mund and the rest of the Ruhr Area. Also from this station, there are connections to the “Technologiepark” and (via South Campus) Eichlinghofen. The other station is located at the dining hall at North Campus and offers a direct connection to South Campus every five minutes.