R with ImageJ can be used perfectly to classify images. Transferred and returned a 16000*16000 image as byte data (grayscale) to R and ImageJ in one shot.Īnd with 64-bit (with a personal OSX port of Bio7).Ĭluster Analysis (clara) with R: Max 7000*6157*3(RGB) -> 6 centers: 168sec. Transferred 8000*8000 image as integer data to R in one shot.
Transferred 7 Landsat images 7457*6991 (byte transfer) and created a new image from the sum of the 7 images (integer conversion! with a triggering of the garbage collector).
Imagej for mac 10.6 windows#
Hardware: AMD Turion 2.0 GHz Dual core, 3Gb RAM Windows Vista 32-bitĬluster Analysis (clara): Max 5000*5000*3(RGB) -> 6 centers: 70sec., 12 centers: 100s (byte transfer!). With the correct image datatype (raw, integer, double) R is also able to handle and process images >2000*2000 pixels (in combination with java!).įor my own curiosity i tried to find out the limits on a 32-bit and 64-bit OS with the image data present in the virtual maschine and after transfer (by means of Rserve) in R, too. But the combination of a scientific image analysis tool like ImageJ with R offers much more possibilities to edit and analyze images.
In general R is a very useful application for image analysis and plenty of “pure” R packages for image analysis are already available. In this post i would like to demonstrate the ability of R to handle and classify image data with the help of ImageJ and Rserve bundled and implemented in Bio7.
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