Not exactly sure how one would put context of what object is more dominant than other. Think of landscape with snow, green mountains and set of flowers of varied colors including a rose....
On Fri, Sep 17, 2010 at 8:43 PM, Shashi Kant <sk...@sloan.mit.edu> wrote: > > > > What I am envisioning (at least to start) is have all this add two fields > in > > the index. One would be for color information for the color similarity > > search. The other would be a simple multivalued text field that we put > > keywords into based on what OpenCV can detect about the image. If it > > detects faces, we would put "face" into this field. Other things that it > > can detect would result in other keywords. > > > > For the color search, I have a few inter-related hurdles. I've got to > > figure out what form the color data actually takes and how to represent > it > > in Solr. I need Java code for Solr that can take an input color value > and > > find similar values in the index. Then I need some code that can go in > our > > feed processing scripts for new content. That code would also go into a > > crawler script to handle existing images. > > > > You are on the right track. You can create a set of representative > keywords from the image. OpenCV gets a color histogram from the image > - you can set the bin values to be as granular as you need, and create > a look-up list of color names to generate a MVF representative of the > image. > If you want to get more sophisticated, represent the colors with > payloads in correlation with the distribution of the color in the > image. > > Another approach would be to segment the image and extract colors from > each. So if you have a red rose with all white background, the textual > representation would be something like: > > white, white.......red.......white, white > > Play around and see which works best. > > HTH >
