CONFIGR (CONtour FIgure and GRound) 1.0

This software has been realized at the CNS Technology Lab at Boston University - http://techlab.bu.edu. The main author of this software is Chaitanya Sai ( http://techlab.bu.edu/members/sai/ ).CONFIGR (CONtour FIgure GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting, and typically incomplete, figure is fed back to the ?early vision? stage for long-range completion via filling-in. The reconstructed image is then re-presented to the recognition system for global functions such as object recognition. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel, whose size defines a computational spatial scale. Once the pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. Open-source CONFIGR code is available online, but all examples can be derived analytically, and the design principles applied at each step are transparent. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Lobe computations occur on a subpixel spatial scale. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects and segments sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images.Code DescriptionMATLAB 7.0 or higher. Usage: I_output = runCONFIGR(I,PixRes) This runs CONFIGR with the following defaults: PixRes: pixel resolution default=1: CONFIGR pixel resolution is the same as that of the input image Advanced Options: I_output = runCONFIGR(I,PixRes,NumIter,ShrinkFact) I: input image PixRes: pixel resolution 1: fine 2: medium 3: coarse The following options provide computational flexibility but are not model parameters. NumIter: number of iterations CONFIGR simulation can be forced to stop early by setting a low number of iterations. ShrinkFact: ratio of desired image size to actual size Sparse images can be resized for faster runtimes. Raw CONFIGR output (ground and figure-filled rectangles, and interpolating diagonals) can be obtained using [I_output, I_output_raw, Idiagonals]=runCONFIGR(I)More info available at http://techlab.bu.edu/resources/software_v...lab_and_c_code/- ContributorsGail CarpenterBen ChandlerRobert KozmaPraveen K. PillyChaitanya SaiDoug SondakKadin Tseng

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Adaptive,  Compressed,  Descriptionmatlab,  Groups,  Higher,  Highly,  Images,  Important,  Intrinsic,  Longrange,  Output,  Processors,  Promises,  Reconstruct,  Runconfigripixres,  Usage,  Video
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