I am looking for someone to develop a fuzzy logic clustering algorithm to classify a given image into targets and backgrounds. The algorithm should form clusters and be trained without supervision. The clustering should be done on the basis of the statistical properties of the set of inputs. The algorithm will feature an adaptive mechanism for selecting the number of clusters, and feature an adaptive threshold.
The algorithm is to be used in an Batch Image Binarization software and must be capable of processing large images ie 10,000 x 10,000 pixels quickly. The images are of historic newspapers in poor condition and often difficult to read in the scanned greyscale images. Input images will be supplied to successful bidder and will be in Tiff (uncompressed greyscale) JPEG and JPEG2000 formats.
I am open to suggestions of what other features should be included in the algorithms
1) Complete and fully-functional working program(s) in executable form as well as complete source code of all work done.
2) Deliverables must be in ready-to-run condition, as follows (depending on the nature of the deliverables):
a) For web sites or other server-side deliverables intended to only ever exist in one place in the Buyer's environment--Deliverables must be installed by the Seller in ready-to-run condition in the Buyer's environment.
b) For all others including desktop software or software the buyer intends to distribute: A software installation package that will install the software in ready-to-run condition on the platform(s) specified in this bid request.
3) All deliverables will be considered "work made for hire" under U.S. Copyright law. Buyer will receive exclusive and complete copyrights to all work purchased. (No GPL, GNU, 3rd party components, etc. unless all copyright ramifications are explained AND AGREED TO by the buyer on the site per the coder's Seller Legal Agreement).