How do I test if jpeg is photo (or rather logo)

I am extracting all images from given PDF files (containing real estate synopses) using the pdfimages tool as jpegs. Now I want to automatically distinguish between photo开发者_开发问答s and other pictures, like maybe the broker's logo. How should I do this?

• Is there an open tool that can distinguish between photos and clipart/line drawings etc. like google image search does?
• Is there an open tool that gives me the number of colors used for a given jpeg?

I know this will bear a certain uncertainty, but that's okay.

I would look at colour distribution. The colours are likely to be densely packed or "too" evenly spread in the case of gradients. Alternatively, you could look at the frequency distribution of the image.

You can solve your problem in two steps: (1) extract some kind of information from the image and (2) train a classifier that can distinguish the two types of images:

1 - Feature Extraction

In this step you will have to write a program/function that takes a image as input and returns a numeric vector to describe its visual information. As koan points out in his answer, the color distribution contains a lot of useful information. So I would try the following measures: * Histogram of each color channel (Red, Green, Blue), as this is a basic description of the color distribution of the image; * Mean, standard deviation and other statistical moments of each histogram. This should give you information on how the colors are distributed in the image. For a drawing, such as logo, the color distribution should be significantly different from a photo; * Fourier Descriptors. In a drawing, you will probably find a lot edges whereas in a photo this is not expected. With fourier descriptors, you can get this kind of information.

2 - Classification

In this step you will train some sort of classifier. Basically, get a set of images and label each one manually as a drawing or a photo. Also, use your extraction function that you wrote in step 1 to extract vectors from each image. This will be your training set. The training set will be used as input to train a classifier. As Neil N commented, a neural network may be an overkill (or maybe not?), but there are a lot of classifier that you can use (e.g. k-NN, SVM, decision trees). You don't have to implement the classifier yourself, as you can use a machine learning software such as Weka.

Finally, after you have trained your classifier, extract the vector from the image you want test. Use this vector as input to the classifier to get a prediction of whether the image is a photo or a logo.

A simpler solution is to automatically send the image to google image search with the 'similar images' setting on, and see if google sends back primarily PNG results or JPEG results.