diff --git a/ext/opencv/mat.cpp b/ext/opencv/mat.cpp
index e17455e..9b6a5ba 100644
--- a/ext/opencv/mat.cpp
+++ b/ext/opencv/mat.cpp
@@ -1260,6 +1260,7 @@ namespace rubyopencv {
       rb_define_method(rb_klass, "threshold", RUBY_METHOD_FUNC(rb_threshold), 3); // in ext/opencv/mat_imgproc.cpp
       rb_define_method(rb_klass, "threshold!", RUBY_METHOD_FUNC(rb_threshold_bang), 3); // in ext/opencv/mat_imgproc.cpp
       rb_define_method(rb_klass, "adaptive_threshold", RUBY_METHOD_FUNC(rb_adaptive_threshold), 5); // in ext/opencv/mat_imgproc.cpp
+      rb_define_method(rb_klass, "adaptive_threshold!", RUBY_METHOD_FUNC(rb_adaptive_threshold_bang), 5); // in ext/opencv/mat_imgproc.cpp
 
       rb_define_method(rb_klass, "save", RUBY_METHOD_FUNC(rb_save), -1);
 
diff --git a/ext/opencv/mat_imgproc.cpp b/ext/opencv/mat_imgproc.cpp
index 48e86cf..d8071a5 100644
--- a/ext/opencv/mat_imgproc.cpp
+++ b/ext/opencv/mat_imgproc.cpp
@@ -519,6 +519,15 @@ namespace rubyopencv {
       return ret;
     }
 
+    cv::Mat* rb_adaptive_threshold_internal(VALUE self, VALUE max_value, VALUE adaptive_method, VALUE threshold_type,
+					    VALUE block_size, VALUE delta, cv::Mat* destptr) {
+      cv::Mat* selfptr = obj2mat(self);
+      cv::adaptiveThreshold(*selfptr, *destptr, NUM2DBL(max_value), NUM2INT(adaptive_method),
+			    NUM2INT(threshold_type), NUM2INT(block_size), NUM2DBL(delta));
+
+      return destptr;
+    }
+
     /*
      * Applies an adaptive threshold to an array.
      *
@@ -536,19 +545,31 @@ namespace rubyopencv {
      */
     VALUE rb_adaptive_threshold(VALUE self, VALUE max_value, VALUE adaptive_method, VALUE threshold_type,
 				VALUE block_size, VALUE delta) {
-      cv::Mat* selfptr = obj2mat(self);
-      cv::Mat* dstptr = NULL;
+      cv::Mat* destptr = new cv::Mat();
       try {
-	dstptr = new cv::Mat();
-	cv::adaptiveThreshold(*selfptr, *dstptr, NUM2DBL(max_value), NUM2INT(adaptive_method),
-			      NUM2INT(threshold_type), NUM2INT(block_size), NUM2DBL(delta));
+	rb_adaptive_threshold_internal(self, max_value, adaptive_method, threshold_type,
+				       block_size, delta, destptr);
       }
       catch (cv::Exception& e) {
-	delete dstptr;
+	delete destptr;
 	Error::raise(e);
       }
 
-      return mat2obj(dstptr, CLASS_OF(self));
+      return mat2obj(destptr, CLASS_OF(self));
+    }
+
+    VALUE rb_adaptive_threshold_bang(VALUE self, VALUE max_value, VALUE adaptive_method, VALUE threshold_type,
+				     VALUE block_size, VALUE delta) {
+      cv::Mat* destptr = obj2mat(self);
+      try {
+	rb_adaptive_threshold_internal(self, max_value, adaptive_method, threshold_type,
+				       block_size, delta, destptr);
+      }
+      catch (cv::Exception& e) {
+	Error::raise(e);
+      }
+
+      return self;
     }
   }
 }
diff --git a/ext/opencv/mat_imgproc.hpp b/ext/opencv/mat_imgproc.hpp
index 50577b8..d95a3f9 100644
--- a/ext/opencv/mat_imgproc.hpp
+++ b/ext/opencv/mat_imgproc.hpp
@@ -26,6 +26,8 @@ namespace rubyopencv {
     VALUE rb_threshold_bang(VALUE self, VALUE threshold, VALUE max_value, VALUE threshold_type);
     VALUE rb_adaptive_threshold(VALUE self, VALUE max_value, VALUE adaptive_method,
 				VALUE threshold_type, VALUE block_size, VALUE delta);
+    VALUE rb_adaptive_threshold_bang(VALUE self, VALUE max_value, VALUE adaptive_method,
+				     VALUE threshold_type, VALUE block_size, VALUE delta);
   }
 }
 
diff --git a/test/test_mat_imgproc.rb b/test/test_mat_imgproc.rb
index 6b008fa..e7bd72b 100755
--- a/test/test_mat_imgproc.rb
+++ b/test/test_mat_imgproc.rb
@@ -703,4 +703,44 @@ class TestCvMat < OpenCVTestCase
     # w.show(Cv::hconcat([m0, m]))
     # Cv::wait_key
   end
+
+  def test_adaptive_threshold_bang
+    m0 = Cv::Mat.new(2, 2, Cv::CV_8U)
+    m0[0, 0] = Cv::Scalar.new(10)
+    m0[0, 1] = Cv::Scalar.new(20)
+    m0[1, 0] = Cv::Scalar.new(30)
+    m0[1, 1] = Cv::Scalar.new(40)
+
+    expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[  0,   0;\n 255, 255]>"
+    m = m0.clone
+    m.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, 0)
+    assert_equal(expected, m.to_s)
+
+    m = m0.clone
+    m.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_GAUSSIAN_C, Cv::THRESH_BINARY, 3, 0)
+    assert_equal(expected, m.to_s)
+
+    assert_raise(TypeError) {
+      m0.adaptive_threshold!(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, 0)
+    }
+    assert_raise(TypeError) {
+      m0.adaptive_threshold!(255, DUMMY_OBJ, Cv::THRESH_BINARY, 3, 0)
+    }
+    assert_raise(TypeError) {
+      m0.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_MEAN_C, DUMMY_OBJ, 3, 0)
+    }
+    assert_raise(TypeError) {
+      m0.adaptive_threshold!(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, DUMMY_OBJ, 0)
+    }
+    assert_raise(TypeError) {
+      m0.adaptive_threshold!(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, DUMMY_OBJ)
+    }
+
+    # m0 = Cv::imread(FILENAME_LENA256x256, 0)
+    # m = m0.clone
+    # m.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 25, 0)
+    # w = Window.new('Original | Binary')
+    # w.show(Cv::hconcat([m0, m]))
+    # Cv::wait_key
+  end
 end