Fake Currency Detection using Image Processing

In recent years, a lot of illegal counterfeiting rings manufacture and sell fake coins and at the same time fake note currency is printed as well, which have caused great loss and damage to the society. Thus it is imperative to be able to detect fake currency. We propose a new approach to detect fake Indian notes using their images. A currency image is represented in the dissimilarity space, which is a vector space constructed by comparing the image with a set of prototypes. Each dimension measures the dissimilarity between the image under consideration and a prototype. In order to obtain the dissimilarity between two images, the local key points on each image are detected and described. Based on the characteristics of the currency, the matched key points between the two images can be identified in an efficient manner. A post processing procedure is further proposed to remove mismatched key points. Due to the limited number of fake currency in real life, SVM is conducted for fake currency detection, so only genuine currency are needed to train the classifier

Design and Implementation of Fake Currency Detection System

In recent years, a lot of illegal counterfeiting rings manufacture and sell fake coins and at the same time fake note currency is printed as well, which have caused great loss and damage to the society. Thus it is imperative to be able to detect fake currency. We propose a new approach to detect fake Indian notes using their images. A currency image is represented in the dissimilarity space, which is a vector space constructed by comparing the image with a set of prototypes. Each dimension measures the dissimilarity between the image under consideration and a prototype. In order to obtain the dissimilarity between two images, the local key points on each image are detected and described. Based on the characteristics of the currency, the matched key points between the two images can be identified in an efficient manner. A post processing procedure is further proposed to remove mismatched key points. Due to the limited number of fake currency in real life, SVM is conducted for fake currency detection, so only genuine currency are needed to train the classifier

Design and Implementation of Fake Currency Detection System

In recent years, a lot of illegal counterfeiting rings manufacture and sell fake coins and at the same time fake note currency is printed as well, which have caused great loss and damage to the society. Thus it is imperative to be able to detect fake currency. We propose a new approach to detect fake Indian notes using their images. A currency image is represented in the dissimilarity space, which is a vector space constructed by comparing the image with a set of prototypes. Each dimension measures the dissimilarity between the image under consideration and a prototype. In order to obtain the dissimilarity between two images, the local key points on each image are detected and described. Based on the characteristics of the currency, the matched key points between the two images can be identified in an efficient manner. A post processing procedure is further proposed to remove mismatched key points. Due to the limited number of fake currency in real life, SVM is conducted for fake currency detection, so only genuine currency are needed to train the classifier

Reconhecimento automático de moedas medievais usando visão por computador

Dissertação de mestrado em Engenharia InformáticaThe use of computer vision for identification and recognition of coins is well studied and of renowned interest. However the focus of research has consistently been on modern coins and the used algorithms present quite disappointing results when applied to ancient coins. This discrepancy is explained by the nature of ancient coins that are manually minted, having plenty variances, failures, ripples and centuries of degradation which further deform the characteristic patterns, making their identification a hard task even for humans. Another noteworthy factor in almost all similar studies is the controlled environments and uniform illumination of all images of the datasets. Though it makes sense to focus on the more problematic variables, this is an impossible premise to find outside the researchers’ laboratory, therefore a problematic that must be approached. This dissertation focuses on medieval and ancient coin recognition in uncontrolled “real world” images, thus trying to pave way to the use of vast repositories of coin images all over the internet that could be used to make our algorithms more robust. The first part of the dissertation proposes a fast and automatic method to segment ancient coins over complex backgrounds using a Histogram Backprojection approach combined with edge detection methods. Results are compared against an automation of GrabCut algorithm. The proposed method achieves a Good or Acceptable rate on 76% of the images, taking an average of 0.29s per image, against 49% in 19.58s for GrabCut. Although this work is oriented to ancient coin segmentation, the method can also be used in other contexts presenting thin objects with uniform colors. In the second part, several state of the art machine learning algorithms are compared in the search for the most promising approach to classify these challenging coins. The best results are achieved using dense SIFT descriptors organized into Bags of Visual Words, and using Support Vector Machine or Naïve Bayes as machine learning strategies.O uso de visão por computador para identificação e reconhecimento de moedas é bastante estudado e de reconhecido interesse. No entanto o foco da investigação tem sido sistematicamente sobre as moedas modernas e os algoritmos usados apresentam resultados bastante desapontantes quando aplicados a moedas antigas. Esta discrepância é justificada pela natureza das moedas antigas que, sendo cunhadas à mão, apresentam bastantes variações, falhas e séculos de degradação que deformam os padrões característicos, tornando a sua identificação dificil mesmo para o ser humano. Adicionalmente, a quase totalidade dos estudos usa ambientes controlados e iluminação uniformizada entre todas as imagens dos datasets. Embora faça sentido focar-se nas variáveis mais problemáticas, esta é uma premissa impossível de encontrar fora do laboratório do investigador e portanto uma problemática que tem que ser estudada. Esta dissertação foca-se no reconhecimento de moedas medievais e clássicas em imagens não controladas, tentando assim abrir caminho ao uso de vastos repositórios de imagens de moedas disponíveis na internet, que poderiam ser usados para tornar os nossos algoritmos mais robustos. Na primeira parte é proposto um método rápido e automático para segmentar moedas antigas sobre fundos complexos, numa abordagem que envolve Histogram Backprojection combinado com deteção de arestas. Os resultados são comparados com uma automação do algoritmo GrabCut. O método proposto obtém uma classificação de Bom ou Aceitável em 76% das imagens, demorando uma média de 0.29s por imagem, contra 49% em 19,58s do GrabCut. Não obstante o foco em segmentação de moedas antigas, este método pode ser usado noutros contextos que incluam objetos planos de cor uniforme. Na segunda parte, o estado da arte de Machine Learning é testado e comparado em busca da abordagem mais promissora para classificar estas moedas. Os melhores resultados são alcançados usando descritores dense SIFT, organizados em Bags of Visual Words e usando Support Vector Machine ou Naive Bayes como estratégias de machine learning

The cultural evolution of coinage as an informational system

The invention of coined money significantly changed economic history, by introducing a convenient and universal medium of exchange, whose value is regulated and guaranteed by a political authority. In order to be used as a means of payment, coins need to be recognized as valid and trustworthy. Combining carefully designed material features with inscriptions and images, they form a system of symbols that store and transmit information, primarily of an economic nature. The aim of this thesis was to investigate how coins encode information, and to understand how historical dynamics and human cognition shaped their evolution as an informational system. These questions were explored over three studies. The first study investigated the influence of changing political and economic circumstances in the ancient Mediterranean (7th - 1st ct. BCE) on the informative role of graphic designs as marks of issuing authority and monetary value. The second study discussed the advantages and challenges of digitization, standardization and quantitative approaches to cultural data, with a focus on coin iconography. The third study examined the representation and perception of monetary value in the properties of contemporary coins. This thesis shows how we can examine the structure and evolution of coins within an interdisciplinary framework, using quantitative methods, combined with insights from evolutionary and cognitive anthropology, and information theory. The increasing availability of expertly curated digital collections opens more possibilities for developing quantitative approaches necessary for proper interpretation of the processes which shaped observed patterns in cultural data. The approach taken in this thesis complements the research in numismatics and economic history on the origins and development of coinage, while also highlighting the possibilities of using historical artefacts to study large-scale patterns in the evolution and transmission of cultural traits

Encapsulated social perception of emotional expressions

In this paper I argue that the detection of emotional expressions is, in its early stages, informationally encapsulated. I clarify and defend such a view via the appeal to data from social perception on the visual processing of faces, bodies, facial and bodily expressions. Encapsulated social perception might exist alongside processes that are cognitively penetrated, and that have to do with recognition and categorization, and play a central evolutionary function in preparing early and rapid responses to the emotional stimuli

Integration of SARS-CoV-2 RNA in infected human cells by retrotransposons: an unlikely hypothesis and old viral relationships

Zhang et al. (Proc Natl Acad Sci 118:e2105968118, 2021) recently reported that SARS-CoV-2 RNA can be retrotranscribed and integrated into the DNA of human cells by the L1 retrotransposon machinery. This phenomenon could cause persistence of viral sequences in patients and may explain the prolonged PCR-positivity of SARS-CoV-2 infected patients, even long after the phase of active virus replication has ended. This commentary does critically review the available data on this topic and discusses them in the context of findings made for other exogenous viruses and ancestral endogenous retroviral elements

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human beings as animate elements of their environment. The interpretation by this human counterpart is critical to the success of the system's integration: knobs on the system need to make sense to a human counterpart; an artificial agent should have a way of notifying a human counterpart of a change in system state, possibly through motion profiles; and the motion of a human counterpart may have important contextual clues for task completion. Thus, professional choreographers, dance practitioners, and movement analysts are critical to research in robotics. They have design methods for movement that align with human audience perception, can identify simplified features of movement for human-robot interaction goals, and have detailed knowledge of the capacity of human movement. This article provides approaches employed by one research lab, specific impacts on technical and artistic projects within, and principles that may guide future such work. The background section reports on choreography, somatic perspectives, improvisation, the Laban/Bartenieff Movement System, and robotics. From this context methods including embodied exercises, writing prompts, and community building activities have been developed to facilitate interdisciplinary research. The results of this work is presented as an overview of a smattering of projects in areas like high-level motion planning, software development for rapid prototyping of movement, artistic output, and user studies that help understand how people interpret movement. Finally, guiding principles for other groups to adopt are posited.Comment: Under review at MDPI Arts Special Issue "The Machine as Artist (for the 21st Century)" http://www.mdpi.com/journal/arts/special_issues/Machine_Artis