diff --git a/ext/opencv/cvmat.cpp b/ext/opencv/cvmat.cpp
index 9735b9a..b4dbd94 100644
--- a/ext/opencv/cvmat.cpp
+++ b/ext/opencv/cvmat.cpp
@@ -309,7 +309,7 @@ void define_ruby_class()
   rb_define_method(rb_klass, "det", RUBY_METHOD_FUNC(rb_det), 0);
   rb_define_alias(rb_klass, "determinant", "det");
   rb_define_method(rb_klass, "invert", RUBY_METHOD_FUNC(rb_invert), -1);
-  rb_define_method(rb_klass, "solve", RUBY_METHOD_FUNC(rb_solve), -1);
+  rb_define_singleton_method(rb_klass, "solve", RUBY_METHOD_FUNC(rb_solve), -1);
   rb_define_method(rb_klass, "svd", RUBY_METHOD_FUNC(rb_svd), -1);
   rb_define_method(rb_klass, "svbksb", RUBY_METHOD_FUNC(rb_svbksb), -1);
   rb_define_method(rb_klass, "eigenvv", RUBY_METHOD_FUNC(rb_eigenvv), -1);
@@ -2801,7 +2801,7 @@ rb_invert(int argc, VALUE *argv, VALUE self)
 
 /*
  * call-seq:
- *   solve(<i>mat, inversion_method=:lu</i>)
+ *   solve(<i>src1, src2, inversion_method=:lu</i>)
  *
  * Solves linear system or least-squares problem (the latter is possible with SVD method).
  *
@@ -2819,13 +2819,13 @@ rb_invert(int argc, VALUE *argv, VALUE self)
 VALUE
 rb_solve(int argc, VALUE *argv, VALUE self)
 {
-  VALUE mat, symbol;
-  rb_scan_args(argc, argv, "11", &mat, &symbol);
+  VALUE src1, src2, symbol;
+  rb_scan_args(argc, argv, "21", &src1, &src2, &symbol);
   VALUE dest = Qnil;
-  CvArr* arr_ptr = CVARR_WITH_CHECK(mat);
+  CvArr* src2_ptr = CVARR_WITH_CHECK(src2);
   try {
-    dest = new_mat_kind_object(cvGetSize(arr_ptr), self);
-    cvSolve(CVARR(self), arr_ptr, CVARR(dest), CVMETHOD("INVERSION_METHOD", symbol, CV_LU));
+    dest = new_mat_kind_object(cvGetSize(src2_ptr), src2);
+    cvSolve(CVARR_WITH_CHECK(src1), src2_ptr, CVARR(dest), CVMETHOD("INVERSION_METHOD", symbol, CV_LU));
   }
   catch (cv::Exception& e) {
     raise_cverror(e);
diff --git a/test/test_cvmat.rb b/test/test_cvmat.rb
index f6aa9d8..3b103ad 100755
--- a/test/test_cvmat.rb
+++ b/test/test_cvmat.rb
@@ -2353,29 +2353,35 @@ class TestCvMat < OpenCVTestCase
     elems2 = [3,
               4,
               5]
-    m0 = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
+    a = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
       CvScalar.new(elems1[c])
     }
     b = create_cvmat(3, 1, :cv32f, 1) { |j, i, c|
       CvScalar.new(elems2[c])
     }
 
-    m1 = m0.solve(b)
-    m2 = m0.solve(b, :lu)
-    m3 = m0.solve(b, :svd)
-    m4 = m0.solve(b, :svd_sym)
-    m5 = m0.solve(b, :svd_symmetric)
+    m1 = CvMat.solve(a, b)
+    m2 = CvMat.solve(a, b, :lu)
+    m3 = CvMat.solve(a, b, :svd)
+    m4 = CvMat.solve(a, b, :svd_sym)
+    m5 = CvMat.solve(a, b, :svd_symmetric)
     expected = [2, -2, 1]
-    [m1, m2, m3, m4, m5].each { |m|
+    [m1, m2, m3].each { |m|
       assert_equal(b.width, m.width)
-      assert_equal(m0.height, m.height)
+      assert_equal(a.height, m.height)
       assert_each_cvscalar(m, 0.001) { |j, i, c|
         CvScalar.new(expected[c])
       }
     }
 
     assert_raise(TypeError) {
-      m0.solve(b, DUMMY_OBJ)
+      CvMat.solve(DUMMY_OBJ, b)
+    }
+    assert_raise(TypeError) {
+      CvMat.solve(a, DUMMY_OBJ)
+    }
+    assert_raise(TypeError) {
+      CvMat.solve(a, b, DUMMY_OBJ)
     }
   end