Here is a hand drawn target image for this texture and here is the source texture sample
We have come up with a way to modify Stanford algorithm so that it works better for a specific class of textures and runs more than an order of magnitude faster (1-2 sec. on 195 MHz R10000 to create a 500x500 image). The class of textures we are most interested in are those consisting of arrangements of small objects of familiar but irregular size, which are very common in nature and include flower fields, leafs, pebbles, tree branches, etc. Surprisingly, the algorithm also does a reasonable job on many textures is was not designed for, such as the one shown above. Some examples can be found below.
Our algorithm is simple to understand and implement but it it was never intended to work for an arbitrary texture. In particular, the original Stanford algorithm usually performs better on smooth textures, such as waves, clouds, etc. If you want to find out whether it works for your favorite texture, I would recommend to simply implement it - this should not take more than a few hours.
A method to provide the user with intuitive control over the synthesis process has also been developed. The user provides a target image and the algorithm attempts to create a texture with large-scale features governed by this target while preserving "texture-like" appearance. The degree of conformance to the target is varied by the number of iterations. The image on the top of this page is an example of this process (two iterations were performed in this case, but usually it takes many more to get a pronounced pattern). While writing text with textures is a fun application, the ability to modify particular area of the result image (poor man's shadows) or to provide some help to the algorithm in a difficult case by giving structural guidance is much more useful. Examples of this can be found below. Of course, for some textures user control works better than for others. Again, the easiest way to find out is to try it.
Details of the algorithm are described in the following paper. Full resolution images from this paper (and they DO look much better large) are available in the example section below. I would also suggest to visit Stanford page which shows their results for these textures and for many others.