Slashdot Mirror

← Back to Stories (view on slashdot.org)

Particle Swarm Optimization for Picture Analysis

Posted by Zonk on from the new-uses-old-techniques dept.

Roland Piquepaille writes "Particle swarm optimization (PSO) is a computer algorithm based on a mathematical model of the social interactions of swarms which was first described in 1995. Now, researchers in the UK and Jordan have carried this swarm approach to photography to 'intelligently boost contrast and detail in an image without distorting the underlying features.' This looks like a clever concept even if I haven't seen any results. The researchers have developed an iterative process where a swarm of images are created by a computer. These images are 'graded relative to each other, the fittest end up at the front of the swarm until a single individual that is the most effectively enhanced.'"

5 of 90 comments (clear)

  1. The only problem... by arrrrg · · Score: 4, Informative

    with PSO, ant colony optimization, genetic algorithms, etc. is that they take tons of computational effort, and typically work no better than (or significantly worse than) much more efficient direct optimization methods. Wake me up if they show good results (esp. that didn't take a year of computer time to construct).

    P.S. IAAAIR (I am an AI researcher, albeit not in computer vision)

    1. Re:The only problem... by TapeCutter · · Score: 3, Informative

      "the fittest end up at the front of the swarm until a single individual that is the most effectively enhanced"

      Actually I think the biggest problem with any of these techniques is finding an algorithmic definition of 'fittest' and 'effectively', the rest can be solved by throwing money at the computation.

      --
      And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
    2. Re:The only problem... by NickBoje · · Score: 3, Informative

      You are hundred and one percent right. PSO works mainly with the help of two arbitrary coefficients which are highly oscillatory. Main effort is involved in selecting those coefficient values, accurately. Very good technique but very few good applications solved ...,

  2. Not exactly comprehensive by vikstar · · Score: 5, Informative

    For more detail, including the citation of the paper, see this http://www.primidi.com/2008/02/03.html

    --
    The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.
  3. Nothing new to see here by kegon · · Score: 3, Informative

    They've reinvented genetic algorithms ?

    Without seeing the details (read TFA but it's a summary and quite a bad one at that), I can't see why this would be better than a Bayesian optimisation with a photometric constraint. "The objective of the algorithm is to maximize the total number of pixels in the edges" sounds very, very simplified.

    There are efficient ways of solving these things. Interesting that they invent an image processing algorithm but publish it in a non image processing journal - I wonder why that is ?