Colorization of Images using Soft Colour Capsule Networks

Ch. Swapnapriya*, G. Josemoses**, K. V. Ramana***
*,*** Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Kakinada, India.
** Guru Nanak University, Ranga Reddy District, Hyderabad, India.
Periodicity:January - March'2023
DOI : https://doi.org/10.26634/jcom.10.4.19313

Abstract

Perceiving and interpreting color phenomena is a complex process for the human brain. Obtaining the true color of an object requires different experimental, physical, and theoretical results. By examining image features, color, and other aspects, individuals can study techniques for applying full-color images. In this context, color chemistry has been used in crime investigations to detect the time of death. It can be challenging for police to physically examine decomposed dead bodies, especially if they have been unknown for days, weeks, or even months. This makes the task much harder for law enforcement officials. An innovative approach has been developed to assist the police in investigating cases more efficiently. This approach enables them to solve crimes from the convenience of their offices, thereby enhancing their productivity.

Keywords

Colorization, Color Capsule Networks, Skin Discolouring.

How to Cite this Article?

Swapnapriya, Ch., Josemoses, G., and Ramana, K. V. (2023). Colorization of Images using Soft Colour Capsule Networks. i-manager’s Journal on Computer Science, 10(4), 9-16. https://doi.org/10.26634/jcom.10.4.19313

References

[1]. Amourizi, F., Dashtian, K., Ghaedi, M., & Hosseinzadeh, B. (2021). An asymmetric Schiff basefunctionalized gold nanoparticle-based colorimetric sensor for Hg 2+ ion determination: Experimental and DFT studies. Analytical Methods, 13(23), 2603-2611. https://doi.org/10.1039/ D1AY00408E
[2]. Chen, H., Song, Y., & Li, X. (2019). A deep learning framework for identifying children with ADHD using an EEGbased brain network. Neurocomputing, 356, 83-96. https://doi.org/10.1016/j.neucom.2019.04.058
[3]. Fuyal, M., & Giri, B. (2020). A combined system of paper device and portable spectrometer for the detection of pesticide residues. Food Analytical Methods, 13(7), 1492-1502. https://doi.org/10.1007/s12161-020-01770-y
[4]. Haider, A., Ahmed, M., Faisal, M., & Naseer, M. M. (2020). Isatin as a simple, highly selective and sensitive colorimetric sensor for fluoride anion. Heterocyclic Communications, 26(1), 14-19. https://doi.org/10.1515/hc-2020-0003
[5]. Lin, B., Yu, Y., Cao, Y., Guo, M., Zhu, D., Dai, J., & Zheng, M. (2018). Point-of-care testing for streptomycin based on aptamer recognizing and digital image colorimetry by smartphone. Biosensors and Bioelectronics, 100, 482-489. https://doi.org/10.1016/j. bios.2017.09.028
[6]. Mahato, K., & Chandra, P. (2019). Paper-based miniaturized immunosensor for naked eye ALP detection based on digital image colorimetry integrated with smartphone. Biosensors and Bioelectronics, 128, 9-16. https://doi.org/10.1016/j.bios.2018.12.006
[7]. Oliveira, G. C., Machado, C. C. S., Inácio, D. K., Petruci, J. F. S., & Silva, S. G. (2022). RGB color sensor for colorimetric determinations: Evaluation and quantitative analysis of colored liquid samples. Talanta, 241, 123244. https://doi.org/10.1016/j.talanta.2022.123244
[8]. Phatthanawiwat, K., Boonkanon, C., Wongniramaikul, W., & Choodum, A. (2022). Catechin and curcumin nanoparticle-immobilized starch cryogels as green colorimetric sensors for on-site detection of iron. Sustainable Chemistry and Pharmacy, 29, 100782. https://doi.org/10.1016/j.scp.2022.100782
[9]. Spica, N., Green, M., Lown, L., Duwal, R., Fuyal, M., Giri, S., ... & Lamichhane-Khadka, R. (2021). Development of a microbiological paper-based analytical device to detect fecal contamination of water in resource-limited settings. Water, Air, & Soil Pollution, 232, 1-12. https://doi.org/10.1007/s11270-021-05132-0
[10]. Tao, Y., Li, M., Kim, B., & Auguste, D. T. (2017). Incorporating gold nanoclusters and target-directed liposomes as a synergistic amplified colorimetric sensor for HER2-positive breast cancer cell detection. Theranostics, 7(4), 899-911. https://doi.org/10.7150/thno.17927
[11]. Taweekarn, T., Wongniramaikul, W., & Choodum, A. (2022). Removal and recovery of phosphate using a novel calcium silicate hydrate composite starch cryogel. Journal of Environmental Management, 301, 113923. https://doi.org/10.1016/j.jenvman.2021.113923
[12]. Urapen, R., & Masawat, P. (2015). Novel method for the determination of tetracycline antibiotics in bovine milk based on digital-image-based colorimetry. International Dairy Journal, 44, 1-5. https://doi.org/10.1016/j.idairyj.2014.12.002
[13]. Wang, K., He, J., & Zhang, L. (2019). Attention-based convolutional neural network for weakly labeled human activities' recognition with wearable sensors. IEEE Sensors Journal, 19(17), 7598-7604. https://doi.org/10.1109/JSEN.2019.2917225
[14]. Zhang, Q., Yu, Y., Yun, X., Luo, B., Jiang, H., Chen, C., ... & Min, D. (2020). Multicolor colorimetric sensor for detection of omethoate based on the inhibition of the enzyme-induced metallization of gold nanorods. ACS Applied Nano Materials, 3(6), 5212-5219. https://doi.org/10.1021/acsanm.0c00641
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