Real animals sound like this

If a friend tries to do an impression of an animal call, how easy is it to work out the animal? Alternatively, how good are different people at making animal noises? If a computer could assess the accuracy of these impressions, it would open up some fun possibilities. Imagine searching a database of animal sounds, or a set of known animals in a nature reserve, simply by doing an appropriate impression. I haven’t been able to find many people researching this topic, but I reckon I’m halfway to solving it. I just need a little extra help with some image analysis. Continue reading →

Gratifyingly, my technique correctly classifies drawings like this as pictures, not maps.

How effectively can a computer distinguish pictures or drawings of organisms from maps of their distribution? Based on my previous thoughts on recognising maps, a simple statistical technique allows a computer to correctly identify 99% of maps from within a training set of 1210 images (including 272 maps). Pleasingly, this classification has only a 0.5% false positive rate.

Pretty good, but in the case of images submitted to the Encyclopaedia of Life, we can do better. If we make a guess as to the original format of the image, and include this into the model, we can correctly separate all 272 maps from the 938 pictures and drawings in my particular dataset. If you want to try it out, the dataset is here, and the R code to perform the classification is near the end of this post.
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How do you get a computer to distinguish pictures like the fallow deer at top from distribution maps (bottom)?

I’ve been writing some code to download freely usable images on the internet for large numbers of organisms – for example, for all species of mammal. The Encyclopedia of Life has done a lot of the hard work already – collecting images from Wikimedia Commons, Flickr, etc., encouraging experts to tag them as trusted, and providing an API for retrieving all the relevant data.

One problem is that a small percentage of the automatically harvested pictures are not pictures of the organism, but maps of its distribution, as seen in the lower picture on the right. Is there a way to automatically identify these as maps, or at least to flag up that they might need checking? Continue reading →