Multi Sensor Image Matching using Super Symmetric Affinity Tensors based HyperGraph Matching
Hari Prasada Raju Kunadharaju1, N. Sandhya2, Raghav Mehra3
1Hari Prasada Raju Kunadharaju, Research scholar from Bhagwant University, Ajmer Vice-President, Wells Fargo Enterprise Global Services.
2N. Sandhya, Professor, Department of Computer Science & Engineering, VNR Vignana Jyothi Institute of Engineering & Technology.
3Raghav Mehra, Associate Professor, Department of Computer Science & Engineering, Bhagwant University Ajmer.
Manuscript received on 10 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 6161-6166 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3764078219/19©BEIESP | DOI: 10.35940/ijrte.B3764.078219
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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: Image Matching technique is regularly on one of the main errands in numerous Photogrammetry and Remote Sensing applications. Based on multi-discipline, the approach of multiple sensor image matching is a novel one established which has vital application in military, civil, medicinal, and certain other domains. However, image matching approach faces numerous challenges, specifically in multi-sensor images where the images are gathered from the different sensor with different intensities, scales, and moments. Thus, a novel image matching approach is introduced in this paper using affinity tensor and HyperGraph Matching (HGM) technique that attempts to overcome certain drawbacks in matching and increases performance accuracy. Hypergraph matching techniques are employed using affinity tensors and consider supersymmetric property during construction. Graphs are constructed using graph theory for both sources, and target image and matching is done using third-order tensors. The experimental outcomes displayed that the proposed technique has good recall, precision, and positive accuracy values compared to the existing two descriptors based and tensor-based matching algorithms.
Keywords: Multi Sensor Images; Image Matching; Super Symmetric; Affinity Tensor; Graph Matching; Third Order
Scope of the Article: Image Security