CRITIQUE ON DIGITAL IMAGE PROCESSING
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Abstract
To know about the explicit area of a subject, literature review plays a vital role for understanding and acquiring more insights. This paper is proposed with content-based image processing. The visual features of an image may include like Shape, Colour, texture and etc., to search through vast image database on end-user’s request. This paper reviews different image processingtechniques namely Digital imaging, Digital image processing, fusion synthesis, image editing and so on. Evaluating these techniques reveals the most promising methods for continued investigation.
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Section
Articles
References
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[2]. M. A. A. Mosleh, A. A. AL-Yamni and A. Gumaei, "An Automatic Nuclei Cells Counting Approach Using Effective Image Processing Methods," 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP), 2019, pp. 865-869, doi: 10.1109/SIPROCESS.2019.8868753.
[3]. W. Xiong, "Research on Fire Detection and Image Information Processing System Based on Image Processing," 2020 International Conference on Advance in Ambient Computing and Intelligence (ICAACI), 2020, pp. 106-109, doi: 10.1109/ICAACI50733.2020.00027.
[4]. C. Tang et al., "Joint Regularized-based Image Reconstruction by Combining Super-Resolution Sinogram for Computed Tomography Imaging," 2020 5th International Conference on Communication, Image and Signal Processing (CCISP), 2020, pp. 188-193, doi: 10.1109/CCISP51026.2020.9273488.
[5]. C. Varma and O. Sawant, "An Alternative Approach to Detect Breast Cancer Using Digital Image Processing Techniques," 2018 International Conference on Communication and Signal Processing (ICCSP), 2018, pp. 0134-0137, doi: 10.1109/ICCSP.2018.8524576.
[6]. A. Sharma and A. Sonker, "Benefaction of Digital Image Processing Techniques in Quality Assessment of Rose Flower," 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2019, pp. 1-5, doi: 10.1109/ICCCNT45670.2019.8944567.
[7]. G. Lu, X. Zhang, W. Ouyang, D. Xu, L. Chen and Z. Gao, "Deep Non-Local Kalman Network for Video Compression Artifact Reduction," in IEEE Transactions on Image Processing, vol. 29, pp. 1725-1737, 2020, doi: 10.1109/TIP.2019.2943214.
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[10]. C. Shao, Y. Chen, F. Xu and S. Wang, "A Kind of Pavement Crack Detection Method Based on Digital Image Processing," 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2019, pp. 397-401, doi: 10.1109/IAEAC47372.2019.8997810.