The Intelligent Genuine Validation beyond Online Buddhist Amulet Market

Lawankorn Mookdarsanit

Abstract


As of the internet global coverage, online market is the most popular way for buying and selling many branches of amulets (both talismans and fetishes). How unfortunate that current e-Commerce does not have a genuine validation of the amulet originality. Either genuine or ungenuine amulets are randomly sold on the online market. The current solution is that an amulet need to be physically validated/checked by the amulet expert(s) (Thai: เซียนพระ) that is not such a flexible transaction. To make the trustiness from amulet collectors (Thai: นักสะสมพระเครื่อง), this paper introduces an intelligent genuine validation of amulets on the online amulet market that changes from physical checking by the experts to logical checking by the intelligent validation. The seller can take an amulet image; the intelligent system autonomously checks the genuine validation of amulet as the product quality assurance. In view of start-up ideology, this system is one of a disruptive way to transform into the new business model that provides the online amulet validation as a service for those hundred-thousand amulet collectors around ASEAN. As the system is trained by the amulet experts, it provides high accuracy higher than 75%. It appears that the intelligent genuine validation based on deep learning can autonomously check the originality of an amulet with some service charge, instead of human’s labor.

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References


“Thai Buddha Amulet,” [Online]. Available: https://en.wikipedia.org/wiki/Thai_Buddha_amulet [Accessed: 7 June 2019].

“Thai Amulet Craze Unacceptable Face of Buddhism,” [Online]. Available: https://www.reuters.com/article/us-thailand-amulets/thai-amulet-craze-unacceptable-face-of-buddhism-idUSBKK18907820070712 [Accessed: 15 July 2019].

C. Jones, “Protection Amulets and Magic Spells of Thailand,” in Newsletter of the Thai Healing Alliance International, vol.9, no.1, pp. 6-8, 2010.

“Amulets 101: an Interview With Amulet Master Taan Tha Prachan,” [Online]. Available: https://www.khaosodenglish.com/life/2014/10/01/1412144690/ [Accessed: 27 August 2019].

“Thai Amulets Real or Fake?,” [Online]. Available: https://www.thaiamuletsales.com/thai-amulets-real-or-fake/ [Accessed: 27 August 2019].

B. Sawangsri, “The Forms of Buddha Images From Votive Tablets to Amulets,” in Journal of Buddhist Studies Chulalongkorn University. Vol.17, No.3, pp. 7-21, 2010. [in Thai].

“How much would you pay for a plastic amulet?” [Online]. Available: https://thethaiger.com/news/much-pay-plastic-amulet [Accessed: 27 August 2019].

P. Mookdarsanit, L. Soimart, M. Ketcham and N. Hnoohom, "Detecting Image Forgery Using XOR and Determinant of Pixels for Image Forensics," The 11th IEEE International Conference on Signal-Image Technology & Internet-Based Systems, Bangkok, 2015, pp. 613-616.

K. H. Rhee, "Forensic Detection Using Bit-Planes Slicing of Median Filtering Image," in IEEE Access, vol. 7, pp. 92586-92597, 2019.

L. Soimart and P. Mookdarsanit, “Gender Estimation of a Portrait: Asian Facial-significance Framework,” The 6th International Conference on Sciences and Social Sciences, Mahasarakham, Thailand, 2016.

B. Yang, J. Cao, R. Ni and Y. Zhang, "Facial Expression Recognition Using Weighted Mixture Deep Neural Network Based on Double-Channel Facial Images," in IEEE Access, vol. 6, pp. 4630-4640, 2018.

P. Mookdarsanit and M. Rattanasiriwongwut, “Location Estimation of a Photo: A geo-signature MapReduce Workflow,” in Engineering Journal, vol.21, no.3, pp.295-308, May 2017.

P. Mookdarsanit and M. Ketcham, “Image Location Estimation of Well-known Places from Multi-source based Information,” The 11th International Symposium on Natural Language Processing, Ayutthaya, Thailand, 2016.

X. Li, M. Larson and A. Hanjalic, "Geo-Distinctive Visual Element Matching for Location Estimation of Images," in IEEE Transactions on Multimedia, vol. 20, no. 5, pp. 1179-1194, May 2018.

L. Soimart and M. Ketcham, “The Segmentation of Satellite Image Using Transport Mean-shift Algorithm,” The 13th International Conference on IT Applications and Management, 2015, pp. 124-128.

L. Soimart and M. Ketcham, “An efficient algorithm for earth surface interpretation from satellite imagery,” in Engineering Journal, vol.20, no.5, pp. 215-228, Nov. 2016.

L. Soimart and M. Ketcham, “Hybrid of Pixel-based and Region-based Segmentation for Geology Exploration from Multi-spectral Remote Sensing,” The 11th International Symposium on Natural Language Processing, Ayutthaya, Thailand, 2016.

P. Mookdarsanit and L. Mookdarsanit, “Contextual Image Classification towards Metadata Annotation of Thai-tourist Attractions,” in ITMSoc Transactions on Information Technology Management, vol.3, no.1, pp. 32-40, 2018.

L. Soimart and P. Mookdarsanit, “Name with GPS Auto-tagging of Thai-tourist Attractions from An Image,” The 2nd Technology Innovation Management and Engineering Science International Conference, Nakhon Pathom, Thailand, 2017, pp. 211-217.

P. Sharma and N. Sharma, "Gesture Recognition System," The 4th International Conference on Internet of Things: Smart Innovation and Usages, Ghaziabad, India, 2019, pp. 1-3.

P. Mookdarsanit and L. Mookdarsanit, “An Automatic Image Tagging of Thai Dance’s Gestures,” Joint Conference on ACTIS & NCOBA, Ayutthaya, Thailand, January 2018, pp. 76-80.

P. Mookdarsanit and L. Mookdarsanit, “A Content-based Image Retrieval of Muay-Thai Folklores by Salient Region Matching,” in International Journal of Applied Computer Technology and Information Systems, vol.7, no.2, pp.21-26, 2018.

C. Yang and H. Wei, "Plant Species Recognition Using Triangle-Distance Representation," in IEEE Access, vol. 7, pp. 178108-178120, 2019.

L. Mookdarsanit and P. Mookdarsanit, " Thai Herb Identification with Medicinal Properties Using Convolutional Neural Network," in Suan Sunandha Science and Technology Journal, vol. 6, no.2, pp. 34-40, 2019.

L. Mookdarsanit and P. Mookdarsanit, “SiamFishNet: The Deep Investigation of Siamese Fighting Fishes,” in International Journal of Applied Computer Technology and Information Systems, vol.8, no.2, pp. 40-46, 2019.

E. Dandil and R. Polattimur, "PCA-Based Animal Classification System," The 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies, Ankara, Turkey, 2018, pp. 1-5.

L. Soimart and P. Mookdarsanit, “Ingredients estimation and recommendation of Thai-foods,” in SNRU Journal of Science and Technology, vol.9, no.2, pp.509-520, Jul. 2017.

P. Mookdarsanit and L. Mookdarsanit, “Name and Recipe Estimation of Thai-desserts beyond Image Tagging,” in Kasembundit Engineering Journal, vol.8, Special Issue, pp.193-203, May. 2018.

S. Turmchokkasam and K. Chamnongthai, "The Design and Implementation of an Ingredient-Based Food Calorie Estimation System Using Nutrition Knowledge and Fusion of Brightness and Heat Information," in IEEE Access, vol. 6, pp. 46863-46876, 2018.

P. Mookdarsanit and M. Rattanasiriwongwut, “MONTEAN Framework: A Magnificent Outstanding Native-Thai and Ecclesiastical Art Network,” in International Journal of Applied Computer Technology and Information Systems, vol.6, no.2, pp.17-22, 2017.

P. Fugthong and P. Meesad, “Buddha Amulet Information Retrieval using Digital Images Combined with Feature Extraction and K-nearest Neighbor Techniques,” in Information Technology Journal, vol.6, no. 2, pp. 34-40, 2013. [in Thai].

W. Kitiyanan and P. Pornpanomchai, “Thai Buddhist Amulet Recognition System,” The 2014 International Conference on Informatics and Advanced Computing, Bangkok, Thailand, 2014, pp. 9-14.

T. Sauthananusuk, C. Charoenlarpnopparut, T. Kondo, P. Bunnum and K. Hirohiko, “Thai Amulet Recognition Using Simple Feature,” The International Conference of Information and Communication Technology for Embedded Systems, Ayutthaya, Thailand, 2014.

T. Sauthananusuk, C. Charoenlarpnopparut, T. Kondo, P. Bunnum and K. Hirohiko, “Thai amulet recognition based-on texture feature analysis,” Annual Conference on Engineering and Technology, Osaka, Japan, 2014, pp. 61-70.

Z. Zou, Z. Shi, Y. Guo and J. Ye, “Object Detection in 20 Years: A Survey,” in arXiv:1905.05055, 2019.


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