Abstract
The main aim of Computer vision is to provide the representation of images which is helpful for a better understanding of Two Dimensional and Three-dimensional world. Considering this, in this paper we proposed a method called cellular logic array processing for Three Dimensional wireframe representation of 3D images. This approach detects the junctions, straight lines, curves, depth of the 3D image and constructs the 3D wireframe model for the given dataset. The proposed algorithm has been evaluated on example-based Synthesis of 3D Object Arrangements dataset, PASCAL 3D+ dataset, and our own medical images dataset. The time complexity of the proposed method is O(n3r3) + O(n3) and the Average processing time is 1.12 s. The number of passes required for converting an input image into a wireframe model is one that is less than the other methods. The proposed method is simpler and has better accuracy compared to other wireframe based methods.
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Acknowledgments
The constant support of Prof. Dr. E. G. Rajan, President, Pentagram Research, and Director, Avatar MedVision US LLC NC USA has resulted to bring the results of the research paper. The authors express their sincere thanks to Mr. Pawan Rao, a Data Scientist in the Pentagram Research Centre, and Hyderabad for his valuable suggestion during the preparation of this research paper.
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Rani, S., Lakhwani, K., Kumar, S. (2021). Three Dimensional Wireframe Model of Medical and Complex Images Using Cellular Logic Array Processing Techniques. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_20
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