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Classification
classification

Classification refers to categorizing or classifying parts of an image into different types, for example **pavement**, **water**, **soil** and **sand**. It often relies on examining an image pixel by pixel and using color or shape information to decide which "class" is the best match. The result is often an image such as this one, which is colored by class: If classification can be automated, using for example the software program [GeniePro](http://geniepro.lanl.gov/), large numbers of photos or large maps can be colored by class, helping to quantify for example "how much wetlands?", "how much oil?" or "how much _Spartina alterniflora?_" ###Spectral classification### Using the ratios of Red, Green, and Blue (and possibly Near-infrared), _spectral classification_ attempts to categorize regions of an image by land type. Read more in [this post by Adam Griffith and students at University of South Carolina - Beaufort](http://publiclaboratory.org/notes/adam-griffith/9-10-2011/students-map-campus-university-south-carolina-beaufort-south) ##Open source classification software## * [Spring](http://www.dpi.inpe.br/spring/) - desktop app, not super user-friendly (see [a tree canopy project using SPRING](http://depts.washington.edu/rsgalwrk/canopy/) by Diane Styers) * [Clashifier](http://github.com/jywarren/clashifier) - web service, in planning stage, not functional ...


Author Comment Last activity Moderation
cfastie "The signature of ripe coconuts might be distinguishable from some of the other things in the photos, but not necessarily everything else in the pho..." | Read more » over 4 years ago
warren "Ned Horning points out that Fiji has a similar open source plugin: http://fiji.sc/Trainable_Weka_Segmentation " | Read more » over 8 years ago
nedhorning "Well done. I've been working a bit with texture to add additional image layers (predictor variables) to the stack for eventual automated classifica..." | Read more » almost 9 years ago
cfastie "Charlie: The images everyone is working on are single photos from the cameras (or multispectral versions). The problematic color variations are wit..." | Read more » almost 9 years ago
ttaylor "the large scale image is here, 2736x3648 pixels. The patch of Trapa that I "trained" on and the patch in the upper center really do have significa..." | Read more » almost 9 years ago
nedhorning "Hi Charlie, The better we can represent the variability of the feature we are trying to classify the more accurate the result should be. In genera..." | Read more » almost 9 years ago
cschweik "Thanks Ned for your ongoing insight and expertise. So one thought I had related to Tom's workflow would be to see if we have a broad scale image t..." | Read more » almost 9 years ago
nedhorning "HI all, I thought I made a comment on this earlier today but apparently I did something wrong (again). It's great to see more people digging into ..." | Read more » almost 9 years ago
cschweik "Hi Tom, Chris, (Tom, I'm Charlie, the UMass Amherst faculty who was out in the canoe with Chris. Thanks for doing this work!) Chris - just to be ..." | Read more » almost 9 years ago
cfastie "Camera orientation and position (relative to the photo scene) is reconstructed when a structure-from-motion model is made using lots of photos take..." | Read more » almost 9 years ago
ttaylor "Chris, that's interesting. That patch is significantly less blue that the training patch. I wonder why. Maybe different specularity? From your ..." | Read more » almost 9 years ago
cfastie "This is great information. In the first GIF, the second largest circle, near the top, has a nice large patch of pure Trapa that appears to be simil..." | Read more » almost 9 years ago
ttaylor "I just posted a research note with my little background study of the usefulness of color for Trapa classification; Here's the link. " | Read more » almost 9 years ago
cfastie "Tom, Both WarnerLkVis7075.JPG and WarnerLkVis7136.JPG are there (case sensitive). Their NIR matches (2214 and 2275) are there too. The NIR images..." | Read more » almost 9 years ago
ttaylor "Chris, some questions for you: 1) Is there a full resolution version of WarnerLkVis7075.jpg and WarnerLkVis7136.jpg somewhere for me to download? ..." | Read more » almost 9 years ago
cfastie "philippg, Ned Horning has been working on these images, and has tried some segmentation approaches, but maybe nothing fractal or with spectral cohe..." | Read more » almost 9 years ago
cfastie "Hi Cynthia, We got several GPS locations from patches of water chestnut, but I have not yet matched up the field descriptions with the GPS coordina..." | Read more » almost 9 years ago
cboettner "This looks very encouraging as a possible tool for those of us trying to locate and control water chestnut. Since I haven't been involved since th..." | Read more » almost 9 years ago
philippg "pretty nice results! it seems like the structural information is more telling than the spectral. did you try to calculate e.g. spatially resolved f..." | Read more » almost 9 years ago
nedhorning "This isn't actually a classification. I was generating different layers from the 4-band (red, green, blue, near-IR) images collected a few weeks ag..." | Read more » almost 9 years ago
cfastie "I think the only areas in the image with waterchestnut present are within the white circles. Other areas that are dark in the classification result..." | Read more » almost 9 years ago
jholmes5 "I want to know more! It seems like there are areas around the canoe which have similar appearance in the gray scale are these water chestnut areas ..." | Read more » almost 9 years ago
cfastie "Yes, I noticed that in your note you mentioned that tallow turns color in the fall and nothing else does. So you won't even need IR to distinguish ..." | Read more » almost 9 years ago
eustatic "chris fastie for president. i think tallow looks like broccoli from up high. it would be interesting to develop a color signature, or some kind o..." | Read more » almost 9 years ago