Generalized segment_image() so it works on any pixel type or array of vectors.

I also changed it's interface slightly.  In particular, I removed the min_diff
parameter and replaced it with an explicit min_size parameter.

dlib/image_transforms/segment_image_abstract.h

@@ -15,31 +15,34 @@ namespace dlib
     void segment_image (
         const in_image_type& in_img,
         out_image_type& out_img,
-        const unsigned long k = 200,
-        const unsigned long min_diff = 0
+        const double k = 200,
+        const unsigned long min_size = 10
     );
     /*!
         requires
             - in_image_type  == an implementation of array2d/array2d_kernel_abstract.h
             - out_image_type == an implementation of array2d/array2d_kernel_abstract.h
-            - in_image_type::type  == an unsigned 8-bit or 16bit integer type. 
+            - in_image_type::type  == Any pixel type with a pixel_traits specialization or a
+              dlib matrix object representing a row or column vector.
             - out_image_type::type == unsigned integer type 
             - is_same_object(in_img, out_img) == false
         ensures
-            - Attempts to segment in_img into regions which have some visual consistency to them.
-              In particular, this function implements the algorithm described in the paper:
-              Efficient Graph-Based Image Segmentation by Felzenszwalb and Huttenlocher.
+            - Attempts to segment in_img into regions which have some visual consistency to
+              them.  In particular, this function implements the algorithm described in the
+              paper: Efficient Graph-Based Image Segmentation by Felzenszwalb and Huttenlocher.
             - #out_img.nr() == in_img.nr()
             - #out_img.nc() == in_img.nc()
             - for all valid r and c:
                 - #out_img[r][c] == an integer value indicating the identity of the segment
                   containing the pixel in_img[r][c].  
-            - The k parameter is a measure used to influence how large the segment regions will
-              be.  Larger k generally results in larger segments being produced.  For a deeper 
-              discussion of the k parameter you should consult the above referenced paper.
-            - Any neighboring segments with an edge between them with a pixel difference <= min_diff 
-              will always be merged.  So making min_diff bigger makes this algorithm more eager
-              to merge neighboring segments.
+            - The k parameter is a measure used to influence how large the segment regions
+              will be.  Larger k generally results in larger segments being produced.  For
+              a deeper discussion of the k parameter you should consult the above
+              referenced paper.
+            - min_size is a lower bound on the size of the output segments.  That is, it is
+              guaranteed that all output segments will have at least min_size pixels in
+              them (unless the whole image contains fewer than min_size pixels, in this
+              case the entire image will be put into a single segment).
     !*/
 
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