Soft Computing Based Ground Target Recognition
Vinod Kumar Bhalla1, Ravinanda Kumar2, Manish Kumar Singla3, Parag Nijhawan4
1Vinod Kumar Bhalla, CSE Department, Thapar Institute of Engineering and Technology, Patiala (India).
2Ravinanda Kumar, CSE Department, Thapar Institute of Engineering and Technology, Patiala (India).
3Manish Kumar Singla, EIE Department, Thapar Institute of Engineering and Technology, Patiala (India).
4Parag Nijhawan, EIE Department, Thapar Institute of Engineering and Technology, Patiala (India).
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5598-5603 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9874038620/2020©BEIESP | DOI: 10.35940/ijrte.F9874.038620
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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: Abstract Target recognition from the data obtained from radars poses great challenge to manual analysis of the target with high speed and accuracy. So to overcome this challenge automatic target recognition system is developed using soft computing machine learning tool. The problem becomes more complex when the images are clicked from various angles. An automated classification scheme is proposed in this paper. Principal Component Analysis is used for feature extraction and to reduce the high dominions in the images data. It is known that principal component analysis is widely used from in various fields like space science. Support vector machine is used as a tool. All major kernel functions are applied to gain the maximum accuracy. This framework is evaluated and found effective as compared to results than other methods.
Keywords: Image Classification, Feature Extraction, PCA.
Scope of the Article: Classification.