Added the segment_image() routine.

dlib/image_transforms.h

@@ -14,6 +14,7 @@
 #include "image_transforms/image_pyramid.h"
 #include "image_transforms/label_connected_blobs.h"
 #include "image_transforms/randomly_color_image.h"
+#include "image_transforms/segment_image.h"
 
 #endif // DLIB_IMAGE_TRANSFORMs_
 

dlib/image_transforms/segment_image_abstract.h

+// Copyright (C) 2011  Davis E. King (davis@dlib.net)
+// License: Boost Software License   See LICENSE.txt for the full license.
+#undef DLIB_SEGMENT_ImAGE_ABSTRACT_H__
+#ifdef DLIB_SEGMENT_ImAGE_ABSTRACT_H__
+
+namespace dlib
+{
+
+// ----------------------------------------------------------------------------------------
+
+    template <
+        typename in_image_type,
+        typename out_image_type
+        >
+    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
+    );
+    /*!
+        requires
+            - in_image_type == is an implementation of array2d/array2d_kernel_abstract.h
+            - out_image_type == is an implementation of array2d/array2d_kernel_abstract.h
+            - image_type::type == an unsigned 8-bit or 16bit integer type. 
+            - 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.
+            - #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.
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+}
+
+#endif // DLIB_SEGMENT_ImAGE_ABSTRACT_H__
+
+