Research on detection techniques for pattern modifications of playing cards used in illegal gambling operations
Joong Lee1, Hongseok Kim2, Tae-Yi Kang2
1Artifical Intelligence BigData Medical Center, Yonsei University Wonju College of Medicine, Wonju-si, Gangwon-do, Republic of Korea.
Abstract:
We investigated pattern-modified marked cards used in fraudulent gambling cases in Korea. These cards are printed with modifications to some of the repeated marks on the back, revealing the hand on the front and enabling fraudsters to deceive their victims. We proposed a method for identifying the modified part by first enhancing the card's color difference using an image processing technique and then calculating the similarity between the repeated basic patterns with a Siamese network. This method is fast and convenient, as it can determine the deformation with only 1 or 2 cards and can be implemented in mobile applications, allowing law enforcement officers to investigate quickly. The proposed method serves as a useful tool to aid document examiners in making judgments, as it does not require expensive equipment and effectively visualizes the alterations.
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