Enhancement Image Intensity of HSV Color Space
I Nyoman Gede Arya Astawa1, I Ketut Gede Darma Putra2, I Made Sudarma3, Rukmi Sari Hartati4
1I Nyoman Gede Arya Astawa, Doctoral Programed of Engineering Science, Faculty of Engineering, Udayana University, Bali, Indonesia.
2I Ketut Gede Darma Putra, Department of Electrical Engineering, Politeknik Negeri Bali, Kampus Bukit Jimbaran, Kuta Selatan, Bali, Indonesia.
3I Made Sudarma, Department of Information of Technology, Faculty of Engineering, Udayana University, Bali, Indonesia.
4Rukmi Sari Hartati, Department of Electrical of Engineering, Faculty of Engineering, Udayana University, Bali, Indonesia.
Manuscript received on 16 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 2583-2585 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B13090982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1309.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One of factor that affects technology in face detecting or recognizing is illumination. Poor lighting can cause difficulty to the system to recognize face. Although it is over exposure or under exposure. By doing color image processing, it supports the system to detect face in a poor lighting condition. This research used lighting intensity normalization method to increase face detection performance. This method can normalize the light intensity especially on the face lighting. We normalize the light intensity through HSV color space. HSV color space has saturation which is amount of light in the image. The method proceed saturation in image to increase face detection performance. Total number of faces we had tested is 286 faces, the system detect 243 faces before intensity normalization proceed. Whereas, after normalization process, it detects more faces which is 279 faces. As we can see, the percentage improvement before to after intensity normalization is 84.97% to 97.55%. This is 12.58% improvement. We can say this method helps face detection to increase it performance.
Keywords: Face Detection, Intensity Normalization, HSV Color Space.
Scope of the Article: Signal and Image Processing