Image Quality Determination of HD Cameras by Using Image Processing

Main Article Content

Sadi Fuat Cankaya Ismail Serkan Uncu


Today, images taken from the digital video camera can be supplied in high quality with very low cost. Film cutting and mounting equipment used in the professional system has been no longer left to the computer. High brand value in direct proportion to the development of new technologies produced by companies with number of HD cameras has increased. The HD camera's shutter speed and aperture diameter are the most important factor determining the quality of HD cameras. Because of two important factors, there has been a need to test the HD cameras. Image processing techniques and mechanical system design has been carried out to determine the camera in HD quality. The three electric motors have been used for movement of the system apparatus. Control of the engine has been provided with micro-controllers and driver hardware equipment.

Article Details

How to Cite
CANKAYA, Sadi Fuat; UNCU, Ismail Serkan. Image Quality Determination of HD Cameras by Using Image Processing. Journal of Multidisciplinary Developments, [S.l.], v. 5, n. 1, p. 8-13, may 2020. ISSN 2564-6095. Available at: <>. Date accessed: 22 sep. 2021.
Natural Sciences - Short Research Paper


[1] Schiilsseiworter: Digitales\/ideoforrnat, 1080p, HD Video, HD,

[2] Sidney F. Ray (2000). "Camera Features". In Ralph Eric Jacobson; et al. Manual of Photography: A Textbook of Photographic and Digital Imaging (Ninth ed.). Focal Press. pp. 131–132. ISBN 0-240-51574-9.

[3] Internet: AForge.NET AForge.NET., 2010. Erişim Tarihi 26/10/2015

[4] Chunchang Xiang , Xinhua Chen , Yuheng Chen, Jiankang Zhou , Weimin Shen MTF measurement and imaging quality evaluation of digital camera with slanted-edge method", Proc. SPIE 7849, Optical Design and Testing IV, 78490A (November 05, 2010); DOI:10.1117/12.869937

[5] Dehnie, S. Digital Image Forensics for Identifying Computer Generated and Digital Camera Images , Image Processing 2006 IEEE International Conference,Atlanta GA , 8-11 Oct. 2006 DOI: 10.1109/ICIP.2006.312849

[6] Yutaka Morita, Yuki Tsushima, Masanobu Yasui, Ryoji Termoz, Junko Ajioka, Kozo Takayama, Evaluation of the Disintegration Time of Rapidly Disintegrating Tablets via a Novel Method Utilizing a CCD Camera , Chemical and Pharmaceutical Bulletin Vol. 50 (2002) DOI: 10.1248/cpb.50.1181

[7] Güraksin, G. E., Köse, U., & Deperlıoğlu, Ö. (2016). Underwater image enhancement based on contrast adjustment via differential evolution algorithm. In 2016 International Symposium on INnovations in Intelligent SysTems and Applications (INISTA) (pp. 1-5). IEEE.

[8] Hemanth, D. J., Deperlioglu, O., & Kose, U. (2020). An enhanced diabetic retinopathy detection and classification approach using deep convolutional neural network. Neural Computing and Applications, 32(3), 707-721.

[9] Deperlioglu, O., & Kose, U. (2018). Practical Method for the Underwater Image Enhancement with Adjusted CLAHE. In 2018 International Conference on Artificial Intelligence and Data Processing (IDAP) (pp. 1-6). IEEE.