Abstract
In this paper, we design an agent-based modeling simulation that represents the solitary behavior in tigers and utilizes it in encoding image information. Our model mainly depends on converting the digital data to a virtual environment with paths classified based on the allocation of the data in the original image. Then, we introduce virtual tigers to the environment to begin the encoding process. Tiger agents are separated from each other, and the algorithm monitors their movements and keeps them away from each other. This separation in the virtual environment allows tigers to encode information that exists in different image parts. Additionally, tigers follow a relative movement style that encodes each tiger’s movement direction based on the previous one. This encoding approach allows particular movements that occur in different directions to be encoded in a similar way. After that, we apply Huffman coding to the chain of movements, the purpose of which is to reduce the size and have a new representation. The experimental findings reveal that we could obtain better results than leading standards in bi-level image compression, including JBIG family methods. Our outcomes strengthen the findings of previous studies that incorporated biological behaviors within agent-based modeling simulations and provide a new abstraction to be utilized in information processing research.
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References
Bons, J., Kegel, A.: On the digital processing and transmission of handwriting and sketching. In: Proceedings of EUROCON, vol. 77, pp. 880–890 (1977)
Dhou, K.: Toward a better understanding of viewers’ perceptions of tag clouds: relative size judgment. Ph.D. thesis, University of North Carolina at Charlotte (2013)
Dhou, K., Cruzen, C.: An innovative chain coding technique for compression based on the concept of biological reproduction: an agent-based modeling approach. IEEE Internet Things J. 6(6), 9308–9315 (2019)
Dhou, K.: A novel agent-based modeling approach for image coding and lossless compression based on the Wolf-Sheep predation model. In: Shi, Y., et al. (eds.) ICCS 2018. LNCS, vol. 10861, pp. 117–128. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93701-4_9
Dhou, K.: An innovative design of a hybrid chain coding algorithm for bi-level image compression using an agent-based modeling approach. Appl. Soft Comput. 79, 94–110 (2019). https://doi.org/10.1016/j.asoc.2019.03.024
Dhou, K.: A new chain coding mechanism for compression stimulated by a virtual environment of a predator-prey ecosystem. Future Gen. Comput. Syst. 102, 650–669 (2020)
Dhou, K., Cruzen, C.: A new chain code for bi-level image compression using an agent-based model of echo location in dolphins. In: The 6th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications (2020), In Press
Dhou, K., Cruzen, C.: A highly efficient chain code for compression using an agent-based modeling simulation of territories in biological beavers. Future Gen. Comput. Syst. 118, 1–13 (2021). https://doi.org/10.1016/j.future.2020.12.016
Dhou, K., Cruzen, C.: An innovative employment of the NetLogo AIDS model in developing a new chain code for compression. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds.) ICCS 2021. LNCS, vol. 12742, pp. 17–25. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77961-0_2
Dhou, K., Cruzen, C.: A creative chain coding technique for bi-level image compression inspired by the netlogo hiv agent-based modeling simulation. J. Comput. Sci. 61, 101613 (2022). https://doi.org/10.1016/j.jocs.2022.101613
Dhou, K., Hadzikadic, M., Faust, M.: Typeface size and weight and word location influence on relative size judgments in tag clouds. J. Visual Lang. Comput. 44, 97–105 (2018)
Dhou, K.K., Kosara, R., Hadzikadic, M., Faust, M.: Size judgment and comparison in tag clouds. In: IEEE Visualization Poster Proceedings (2013)
Freeman, H.: On the encoding of arbitrary geometric configurations. IRE Trans. Electron. Comput. 2, 260–268 (1961)
Howard, P.G., Kossentini, F., Martins, B., Forchhammer, S., Rucklidge, W.J.: The emerging JBIG2 standard. IEEE Trans. Circuits Syst. Video Technol. 8(7), 838–848 (1998)
Hwang, Y.T., Wang, Y.C., Wang, S.S.: An efficient shape coding scheme and its codec design. In: Signal Processing Systems, 2001 IEEE Workshop on, pp. 225–232. IEEE (2001)
ISO CCITT Recommend. T.4: Standardization of group 3 facsimile apparatus for document transmission (1980)
Liu, Y.K., Žalik, B.: An efficient chain code with Huffman coding. Pattern Recogn. 38(4), 553–557 (2005)
Mouring, M., Dhou, K., Hadzikadic, M.: A novel algorithm for bi-level image coding and lossless compression based on virtual ant colonies. In: 3rd International Conference on Complexity, Future Information Systems and Risk, pp. 72–78. Setúbal, Portugal (2018)
Recommendation T6. Facsimile Coding Schemes and Coding Control Functions for Group 4 Facsimile Apparatus. International Telecommunication Union, Geneva (1988)
Standards/International Electrotechnical Commission, I.O., et al.: Progressive bilevel image compression. International Standard 11544 (1993)
Sunquist, M.: What is a tiger? ecology and behavior. In: Tilson, R., Nyhus, P.J. (eds.) Tigers of the World (Second Edition). Noyes Series in Animal Behavior, Ecology, Conservation, and Management, pp. 19–33, William Andrew Publishing, Boston, 2nd edn (2010). https://doi.org/10.1016/B978-0-8155-1570-8.00002-5, http://www.sciencedirect.com/science/article/pii/B9780815515708000025
Szokalski, M.S., Litchfield, C.A., Foster, W.K.: Enrichment for captive tigers (panthera tigris): current knowledge and future directions. Appl. Anim. Behav. Sci. 139(1), 1 – 9 (2012). https://doi.org/10.1016/j.applanim.2012.02.021, http://www.sciencedirect.com/science/article/pii/S0168159112000718
Zahir, S., Dhou, K.: A new chain coding based method for binary image compression and reconstruction. In: Picture Coding Symposium, pp. 1321–1324 (2007)
Zhou, L.: A new highly efficient algorithm for lossless binary image compression. ProQuest (2007)
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Dhou, K., Cruzen, C. (2022). A Hypothetical Agent-Based Model Inspired by the Abstraction of Solitary Behavior in Tigers and Its Employment as a Chain Code for Compression. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_13
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