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Development of colorization of grayscale images using CNN-SVM

Abualola, Abdallah and Gunawan, Teddy Surya and Kartiwi, Mira and Ambikairajah, Eliathamby and Habaebi, Mohamed Hadi (2021) Development of colorization of grayscale images using CNN-SVM. In: Advances in Robotics, Automation and Data Analytics. Advances in Intelligent Systems and Computing, Chapter 6 . Springer, pp. 50-58. ISBN 978-3-030-70916-7

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Nowadays, there is a growing interest in colorizing many grayscales or black and white images dating back to before the colored camera for historical and aesthetic reasons. Image and video colorization can be applied to historical images, natural images, astronomical photography. This paper proposes a fully automated image colorization using a deep learning algorithm. First, the image dataset was selected for training and testing purposes. A convolutional neural network (CNN) was designed with several layers of convolutional and max pooling. Support Vector Machine (SVM) regression was used at the final stage. The proposed algorithm was implemented using Python with Keras and Tensorflow libraries in Google Colab. Results showed that the proposed system could predict the colored image from the training process's learning knowledge. A survey was then conducted to validate our findings.

Item Type: Book Chapter
Additional Information: 5588/88884
Uncontrolled Keywords: grayscale image, color image, convolutional neural networks, SVM regression.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology
Depositing User: Prof. Dr. Teddy Surya Gunawan
Date Deposited: 18 Mar 2021 17:21
Last Modified: 28 Jun 2021 16:35
URI: http://irep.iium.edu.my/id/eprint/88884

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