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diff --git a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
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+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/NormalizePlanarYUVLayer.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class NormalizePlanarYUVLayerValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape0, TensorShape shape1, DataType dt)
+    {
+        _data_type = dt;
+        _target    = compute_target(shape0, shape1, dt);
+        _reference = compute_reference(shape0, shape1, dt);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&src_tensor, U &&mean_tensor, U &&sd_tensor)
+    {
+        if(is_data_type_float(_data_type))
+        {
+            float min_bound = 0.f;
+            float max_bound = 0.f;
+            std::tie(min_bound, max_bound) = get_normalize_planar_yuv_layer_test_bounds<T>();
+            std::uniform_real_distribution<> distribution(min_bound, max_bound);
+            std::uniform_real_distribution<> distribution_sd(0, max_bound);
+            library->fill(src_tensor, distribution, 0);
+            library->fill(mean_tensor, distribution, 1);
+            library->fill(sd_tensor, distribution_sd, 2);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType dt)
+    {
+        // Create tensors
+        TensorType src  = create_tensor<TensorType>(shape0, dt, 1);
+        TensorType dst  = create_tensor<TensorType>(shape0, dt, 1);
+        TensorType mean = create_tensor<TensorType>(shape1, dt, 1);
+        TensorType sd   = create_tensor<TensorType>(shape1, dt, 1);
+
+        // Create and configure function
+        FunctionType norm;
+        norm.configure(&src, &dst, &mean, &sd);
+
+        ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(mean.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(sd.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        dst.allocator()->allocate();
+        mean.allocator()->allocate();
+        sd.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!mean.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!sd.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src), AccessorType(mean), AccessorType(sd));
+
+        // Compute function
+        norm.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, DataType dt)
+    {
+        // Create reference
+        SimpleTensor<T> ref_src{ shape0, dt, 1 };
+        SimpleTensor<T> ref_mean{ shape1, dt, 1 };
+        SimpleTensor<T> ref_sd{ shape1, dt, 1 };
+
+        // Fill reference
+        fill(ref_src, ref_mean, ref_sd);
+
+        return reference::normalize_planar_yuv_layer(ref_src, ref_mean, ref_sd);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    DataType        _data_type{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class NormalizePlanarYUVLayerValidationFixture : public NormalizePlanarYUVLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape0, TensorShape shape1, DataType dt)
+    {
+        NormalizePlanarYUVLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE */