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📁 A general technique for the recovery of signi cant image features is presented. The technique is ba
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Color Image SegmentationThis is the implementation of the algorithm described in D. Comaniciu, P. Meer, Robust Analysis of Feature Spaces: Color Image Segmentation,http://www.caip.rutgers.edu/~meer/RIUL/PAPERS/feature.ps.gzappeared in Proceedings of CVPR'97, San Juan, Puerto Rico.================================================================================      Module: README===== -------------------------------------------------------------- ===========      Version 01   Date: 04/22/97===== -------------------------------------------------------------- ======================================================================================      Written by Dorin Comaniciu=====      e-mail:  comanici@caip.rutgers.edu===========================================================================Permission to use, copy, or modify this software and its documentationfor educational and research purposes only is hereby granted withoutfee, provided that this copyright notice appear on all copies andrelated documentation.  For any other uses of this software, in originalor modified form, including but not limited to distribution in wholeor in part, specific prior permission must be obtained fromthe author(s).THE SOFTWARE IS PROVIDED "AS-IS" AND WITHOUT WARRANTY OF ANY KIND,EXPRESS, IMPLIED OR OTHERWISE, INCLUDING WITHOUT LIMITATION, ANYWARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.IN NO EVENT SHALL RUTGERS UNIVERSITY BE LIABLE FOR ANY SPECIAL,INCIDENTAL, INDIRECT OR CONSEQUENTIAL DAMAGES OF ANY KIND, OR ANYDAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,WHETHER OR NOT ADVISED OF THE POSSIBILITY OF DAMAGE, AND ON ANYTHEORY OF LIABILITY, ARISING OUT OF OR IN CONNECTION WITH THE USEOR PERFORMANCE OF THIS SOFTWARE.===========================================================================Source is available from  http://www.caip.rutgers.edu/~meer/RIUL/uploads.htmlThis is an alpha version of the code.The code works with ppm images only.The package contains the following files:  README       - this file  segm_main.cc - input/output operations  segm.cc      - the segmenter  segm.hh      - the header fileTo compile use:  g++ -O2 -o segm segm.cc segm_main.cc -lmI tested the code on:  IRIX Release 5.3 IP22 (Silicon Graphics)  SunOS 5.5 Generic sun4u  Digital UNIX V4.0 (Rev. 386)In addition, the code can be compiled with the CC compiler on   SunOS 5.5 Generic sun4uusing:  CC  -O2 -o segm segm.cc segm_main.cc -lmUsage:   segm image_name.ppmThis version of the code offers three segmentation classes, called  Undersegmentation - lowest resolution       (u)  Oversegmentation  - intermediate resolution (o)  Quantization      - highest resolution      (q)In addition, the program detects the most important color inside one or more given windows (w).The output consists of 2 images:   result.ppm - the segmented version of the input image;  result.pgm - the associated contour image.The output is displayed using the xv.Please send questions or/and comments to  comanici@caip.rutgers.edu

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