Blur Detection and Classification using Dnn
S.Nachiyappan1, Pradeep KV2, K.Anusha3
1Nachiyappan S. * Asst. Prof.(Sr), SCOPE, VIT University, Chennai.
2Pradeep K V, Asst. Prof, SCOPE, VIT University, Chennai.
3Anusha K. Assoc. Prof. SCOPE, VIT University, Chennai.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 26, 2020. | Manuscript published on March 30, 2020. | PP: 4777-4780 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9920038620/2020©BEIESP | DOI: 10.35940/ijrte.F9920.038620
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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: The main goal of blur detection and classification of images using DNN with tensorflow and Keras network. It is to detect and classify an image with natural blur, artificial blur and distorted. As this paper has been a survey and an algorithm has been proposed and implemented, so has to detect and classify accordingly. The proposed algorithm has been implemented and its accuracy has been increased as compared to the existing model of classifying images.
Keywords: Blur Detection, Classification, Identification, Natural Blur, Artificial Blur, Distortion, DNN, Tensorflow
Scope of the Article: Classification.