Image Segmentation and Semantic Labeling using Machine Learning
Abhishek Thakur1, Rajeev Ranjan2
1Abhishek Thakur, Department of Electronics & Communication Engineering, Thapar Institute of Engineering and Technology, Patiala (Punjab), India.
2Rajeev Ranjan, Department of Electronics & Communication Engineering, Thapar Institute of Engineering and Technology, Patiala (Punjab), India.
Manuscript received on 06 February 2019 | Revised Manuscript received on 19 February 2019 | Manuscript Published on 04 March 2019 | PP: 268-272 | Volume-7 Issue-5S2 January 2019 | Retrieval Number: ES2045017519/19©BEIESP
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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: In this paper image color segmentation is performed using machine learning and semantic labeling is performed using deep learning. This process is divided into two algorithms. In the first algorithm machine learning is used to detect super pixels. These super pixels are segmented on the basis of colors. In the second algorithm deep learning is used to train color categories. This algorithm classify each object into semantic labels. Experiment is performed on BSDS300, CASIA v1.0, CASIA v2.0, DVMM and SegNetVGG16CamVid.
Keywords: Feature Extraction; Machine Learning; Deep Learning; Convolution Neural Network; Image Forensic.
Scope of the Article: Machine Learning