Multiple generation of Bengali static signatures

Handwritten signature datasets are really necessary for the purpose of developing and training automatic signature verification systems. It is desired that all samples in a signature dataset should exhibit both inter-personal and intra-personal variability. A possibility to model this reality seems to be obtained through the synthesis of signatures. In this paper we propose a method based on motor equivalence model theory to generate static Bengali signatures. This theory divides the human action to write mainly into cognitive and motor levels. Due to difference between scripts, we have redesigned our previous synthesizer [1,2], which generates static Western signatures. The experiments assess whether this method can approach the intra and inter-personal variability of the Bengali-100 Static Signature DB from a performance-based validation. The similarities reported in the experimental results proof the ability of the synthesizer to generate signature images in this script

Offline Handwriting Signature Verification: A Transfer Learning and Feature Selection Approach

Handwritten signature verification poses a formidable challenge in biometrics and document authenticity. The objective is to ascertain the authenticity of a provided handwritten signature, distinguishing between genuine and forged ones. This issue has many applications in sectors such as finance, legal documentation, and security. Currently, the field of computer vision and machine learning has made significant progress in the domain of handwritten signature verification. The outcomes, however, may be enhanced depending on the acquired findings, the structure of the datasets, and the used models. Four stages make up our suggested strategy. First, we collected a large dataset of 12600 images from 420 distinct individuals, and each individual has 30 signatures of a certain kind (All authors signatures are genuine). In the subsequent stage, the best features from each image were extracted using a deep learning model named MobileNetV2. During the feature selection step, three selectors neighborhood component analysis (NCA), Chi2, and mutual info (MI) were used to pull out 200, 300, 400, and 500 features, giving a total of 12 feature vectors. Finally, 12 results have been obtained by applying machine learning techniques such as SVM with kernels (rbf, poly, and linear), KNN, DT, Linear Discriminant Analysis, and Naive Bayes. Without employing feature selection techniques, our suggested offline signature verification achieved a classification accuracy of 91.3%, whereas using the NCA feature selection approach with just 300 features it achieved a classification accuracy of 97.7%. High classification accuracy was achieved using the designed and suggested model, which also has the benefit of being a self-organized framework. Consequently, using the optimum minimally chosen features, the proposed method could identify the best model performance and result validation prediction vectors.Comment: 11 page

Automatic intrapersonal variability modeling for offline signature augmentation

Orientador: Luiz Eduardo Soares de OliveiraCoorientadores: Robert Sabourin e Alceu de Souza Britto Jr..Tese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 19/07/2021Inclui referências: p. 93-102Área de concentração: Ciência da ComputaçãoResumo: Normalmente, em um cenario do mundo real, poucas assinaturas estao disponiveis para treinar um sistema de verificacao automatica de assinaturas (SVAA). Para resolver esse problema, diversas abordagens para a duplicacao de assinaturas estaticas foram propostas ao longo dos anos. Essas abordagens geram novas amostras de assinaturas sinteticas aplicando algumas transformacoes na imagem original da assinatura. Algumas delas geram amostras realistas, especialmente o duplicator. Este metodo utiliza um conjunto de parametros para modelar o comportamento do escritor (variabilidade do escritor) ao assinar. No entanto, esses parametros so empiricamente definidos. Este tipo de abordagem pode ser demorado e pode selecionar parametros que nao descrevem a real variabilidade do escritor. A principal hipotese desse trabalho e que a variabilidade do escritor observada no dominio da imagem tambem pode ser transferido para o dominio de caracteristicas. Portanto, este trabalho propoe um novo metodo para modelar automaticamente a variabilidade do escritor para a posterior duplicacao de assinaturas no dominio de imagem (duplicator) e dominio de caracteristicas (filtro Gaussiano e variacao do metodo de Knop). Este trabalho tambem propoe um novo metodo de duplicacao de assinaturas estaticas, que gera as amostras sinteticas diretamente no dominio de caracteristicas usando um filtro Gaussiano. Alem disso, uma nova abordagem para avaliar a qualidade de amostras sinteticas no dominio de caracteristicas e apresentada. As limitacoes e vantagens de ambas as abordagens de duplicacao de assinaturas tambem sao exploradas. Alem de usar a nova abordagem para avaliar a qualidade das amostras, o desempenho de um SVAA e avaliado usando as amostras e tres bases de assinaturas estaticas bem conhecidas: a GPDS-300, a MCYT-75 e a CEDAR. Para a mais utilizada, GPDS-300, quando o classificador SVM foi treinando com somente uma assinatura genuina por escritor, ele obteve um Equal Error Rate (EER) de 5,71%. Quando o classificador tambem utilizou as amostras sinteticas geradas no dominio de imagem, o EER caiu para 1,08%. Quando o classificador foi treinado com as amostras geradas pelo filtro Gaussiano, o EER caiu para 1,04%.Abstract: Normally, in a real-world scenario, there are few signatures available to train an automatic signature verification system (ASVS). To address this issue, several offline signature duplication approaches have been proposed along the years. These approaches generate a new synthetic signature sample applying some transformations in the original signature image. Some of them generate realistic samples, specially the duplicator. This method uses a set of parameters to model the writer's behavior (writer variability) during the signing act. However, these parameters are empirically defined. This kind of approach can be time consuming and can select parameters that do not describe the real writer variability. The main hypothesis of this work is that the writer variability observed in the image space can be transferred to the feature space as well. Therefore, this work proposes a new method to automatically model the writer variability for further signature duplication in the image (duplicator) and the feature space (Gaussian filter and a variation of Knop's method). This work also proposes a new offline signature duplication method, which directly generates the synthetic samples in the feature space using a Gaussian filter. Furthermore, a new approach to assess the quality of the synthetic samples in the feature space is introduced. The limitations and advantages of both signature augmentation approaches are also explored. Despite using the new approach to assess the quality of the samples, the performance of an ASVS was assessed using them and three well-known offline signature datasets: GPDS-300, MCYT-75, and CEDAR. For the most used one, GPDS-300, when the SVM classifier was trained with only one genuine signature per writer, it achieved an Equal Error Rate (EER) of 5.71%. When the classifier also was trained with the synthetic samples generated in the image space, the EER dropped to 1.08%. When the classifier was trained using the synthetic samples generated by the Gaussian filter, the EER dropped to 1.04%

iDeLog: Iterative Dual Spatial and Kinematic Extraction of Sigma-Lognormal Parameters

The Kinematic Theory of rapid movements and its associated Sigma-Lognormal model have been extensively used in a large variety of applications. While the physical and biological meaning of the model have been widely tested and validated for rapid movements, some shortcomings have been detected when it is used with continuous long and complex movements. To alleviate such drawbacks, and inspired by the motor equivalence theory and a conceivable visual feedback, this paper proposes a novel framework to extract the Sigma-Lognormal parameters, namely iDeLog. Specifically, iDeLog consists of two steps. The first one, influenced by the motor equivalence model, separately derives an initial action plan defined by a set of virtual points and angles from the trajectory and a sequence of lognormals from the velocity. In the second step, based on a hypothetical visual feedback compatible with an open-loop motor control, the virtual target points of the action plan are iteratively moved to improve the matching between the observed and reconstructed trajectory and velocity. During experiments conducted with handwritten signatures, iDeLog obtained promising results as compared to the previous development of the Sigma-Lognormal.Comment: Accepted Version published by Transactions on Pattern Analysis and Machine Intelligenc

Learning features for offline handwritten signature verification

Handwritten signatures are the most socially and legally accepted means for identifying a person. Over the last few decades, several researchers have approached the problem of automating their recognition, using a variety of techniques from machine learning and pattern recognition. In particular, most of the research effort has been devoted to obtaining good feature representations for signatures, by designing new feature extractors, as well as experimenting with feature extractors developed for other purposes. To this end, researchers have used insights from graphology, computer vision, signal processing, among other areas. In spite of the advancements in the field, building classifiers that can separate between genuine signatures and skilled forgeries (forgeries made targeting a particular individual) is still an open research problem. In this thesis, we propose to address this problem from another perspective, by learning the feature representations directly from signature images. The hypothesis is that, in the absence of a good model of the data generation process, it is better to learn the features from data. As a first contribution, we propose a method to learn Writer-Independent features using a surrogate objective, followed by training Writer-Dependent classifiers using the learned features. Furthermore, we define an extension that allows leveraging the knowledge of skilled forgeries (from a subset of users) in the feature learning process. We observed that such features generalize well to new users, obtaining state-of-the-art results on four widely used datasets in the literature. As a second contribution, we investigate three issues of signature verification systems: (i) learning a fixed-sized vector representation for signatures of varied size; (ii) analyzing the impact of the resolution of the scanned signatures in system performance and (iii) how features generalize to new operating conditions with and without fine-tuning. We propose methods to handle signatures of varied size and our experiments show results comparable to state-of-theart while removing the requirement that all input images have the same size. As a third contribution, we propose to formulate the problem of signature verification as a meta-learning problem. This formulation also learns directly from signatures images, and allows the direct optimization of the objective (separating genuine signatures and skilled forgeries), instead of relying on surrogate objectives for learning the features. Furthermore, we show that this method is naturally extended to formulate the adaptation (training) for new users as one-class classification. As a fourth contribution, we analyze the limitations of these systems in an Adversarial Machine Learning setting, where an active adversary attempts to disrupt the system. We characterize new threats posed by Adversarial Examples on a taxonomy of threats to biometric systems, and conduct extensive experiments to evaluate the success of attacks under different scenarios of attacker’s goals and knowledge of the system under attack. We observed that both systems that rely on handcrafted features, as well as those using learned features, are susceptible to adversarial attacks in a wide range of scenarios, including partial-knowledge scenarios where the attacker does not have full access to the trained classifiers. While some defenses proposed in the literature increase the robustness of the systems, this research highlights the scenarios where such systems are still vulnerable

Literature and Politics in the Age of Nationalism: The Progressive Writers' Movement in South Asia 1932-1956.

This thesis provides an account of the development of the Progressive Writers' Association (PWA) in South Asia. This body set itself the ambitious goal of mobilising South Asian writers and advancing the movement for independence by infusing it with social content. As such it was inspired by movements in Europe but was also inextricably linked to social and literary traditions that had already been developing in India. In this sense the PWA was embarking on a project for cultural hegemony that was as much a political and social movement as a literary one. Consequently, the movement was not solely concerned with questions of literature in a narrow sense but also with the public and political role of writers in society, with which language the nationalist movement should foster and the popularisation of its cultural and political aims through theatre and film. Previous studies of the movement have treated it far too narrowly as a simple front for communist aims. This was an important dimension of the movement that I account for but I see it as an attempt by some of the foremost intellectuals in the India of my period to shape the freedom movement and to project its vision for a wider society post-independence. This thesis argues that the PWA embarked upon a project for cultural and political hegemony whose aim was to transform the literary and wider cultural landscape of South Asia. It aims to demonstrate that the trajectory of this literary project can only be understood as part of a wider process of the global politics that were impacting on the intelligentsia. This thesis is an effort to understand the specific motivations and factors that influenced writers in one of the most turbulent periods of South Asian history. In investigating the interplay between literature and politics there is an assessment of the success and limitations of a cultural movement that aspired to hegemony

Investigating the Common Authorship of Signatures by Off-line Automatic Signature Verification without the Use of Reference Signatures

In automatic signature verification, questioned specimens are usually compared with reference signatures. In writer-dependent schemes, a number of reference signatures are required to build up the individual signer model while a writer-independent system requires a set of reference signatures from several signers to develop the model of the system. This paper addresses the problem of automatic signature verification when no reference signatures are available. The scenario we explore consists of a set of signatures, which could be signed by the same author or by multiple signers. As such, we discuss three methods which estimate automatically the common authorship of a set of off-line signatures. The first method develops a score similarity matrix, worked out with the assistance of duplicated signatures; the second uses a feature-distance matrix for each pair of signatures; and the last method introduces pre-classification based on the complexity of each signature. Publicly available signatures were used in the experiments, which gave encouraging results. As a baseline for the performance obtained by our approaches, we carried out a visual Turing Test where forensic and non-forensic human volunteers, carrying out the same task, performed less well than the automatic schemes

Text, Orality, and Performance in Newar Devotional Music

Dāphā bhajan is a style of devotional song performance practised by Newar men in the towns of the Kathmandu Valley. Although it is now primarily the farming community who maintain it, it originated in the court culture of the Newar kings in the 17th and 18th centuries, and reflects the interests of aristocratic society at that time in devotional literature and music theory. Texts of dāphā songs include compositions attributed to the kings themselves, in old Newari and Maithili, and poetry by Indian authors including Vidyāpati, Nāmdev, Kabīr, Sūrdās and Jayadeva. Transmission to the farming community, among whom literacy and knowledge of the languages concerned were limited, has shifted the balance of attention away from the texts themselves towards the processes of musical performance. As in some other South Asian singing traditions, the generation of intensity through music overwhelms the text, which loses its centrality, its form and even its meaning. The manuscript songbook from which a group sings can no longer be regarded as the vehicle of a written tradition: it is but one element in an oral performance tradition

Sikh Patronage of Hindustani Music and Śabad Kīrtan in Colonial Punjab, 1857-1947

Despite cohabiting overlapping social spheres, north India’s music traditions are too often studied in isolation from one another, negating their inherent interrelatedness. Adopting a more inclusive approach with regard to two major traditions of north India, in this study I explore how both Hindustani music and śabad kīrtan, the sacred music of the Sikhs, enjoyed patronage under the prolific network of Sikh patrons that comprised an important aspect of colonial Punjab’s sociocultural landscape. The distinct influence of aspects of Punjabi society and culture, the unique circumstances surrounding the rise of Sikh patronage, combined with the prominent place of rāg music in Sikh religious tradition, gave rise to an unparalleled environment of music patronage that challenges many modern assumptions about the nature of Hindustani music and its social context during the colonial period. Attending to the Sikh courtly sphere, my study highlights how the developments of Hindustani music in colonial Punjab relate to the broader geopolitics surrounding the 1857 rebellion, harbouring critical insights in relation to the emergence of modern Punjabiyat. Exploring the circulation of Gurmukhi manuscripts on musicology in the Sikh religious sphere up until the late nineteenth century, I highlight a localised tradition of Hindustani musicology, its multivalent character, and links to local music practice. In response to the radical political and discursive shifts wrought by colonialism, I show how in the early twentieth century, through the novel medium of print, the musicological literary output of the Sikhs was co-opted under the new label of gurmat saṅgīt, functioning as a form of symbolic capital in process of Sikh identity formation. Finally, drawing on ethnographic as well as archival research on both sides of the Indo-Pak border, I highlight the multidimensional role of the rabābīs within Sikh religious tradition historically, thus challenging modern musicology-centric understandings of the śabad kīrtan tradition in the process. Attempting to transcend postcolonial discourse and boundaries, this thesis offers a lens through which we might better understand the significant intersection between music traditions in a region like Punjab whilst also offering an alternative perspective on prevailing conceptions of Punjabiyat

Felicity, Trinidad: the musical portrait of a Hindu village

This thesis is based on musicological field work conducted during three visits (1974, 1975, 1977) to Felicity, a village situated in the savannah land of the eastern coast of Trinidad. From 1845 to 1917, East Indian indentured labourers were brought to work on the sugar-cane plantations of several West Indian islands, and their descendants now constitute over one-third the population of Trinidad. The villagers of Felicity, nearly all Hindus, have a musical repertory based almost entirely on north Indian genres. The founders of the village came mainly from eastern Uttar Pradesh, and traditional Bhojpuri folk songs and drumming styles from this region have been passed on in oral tradition and are still performed in the village today. These include byah ke git and lacharl sung at weddings, sohar sung at the birth of a child, lullabies, and songs for the cultivation of rice, as well as repertories and performing practices for the dholak (double-headed barrel drum) and tassa (kettledrum).Music is performed in the three village temples to accompany the sandhya and havan services as well as puja services for the various Hindu deities. The vocal forms include bhaj an, kirtan, and dhun (all sung in Hindi),and Vedic chant (in Sanskrit) . Some of the bhajans (devotional songs in strophic form) have been passed down in oral tradition since the indenture period, but most have been newly introduced to Trinidad either by missionaries from the Indiabased Arya Samaj and Bharat Sevashram Sangha (from the 1920's onwards) or through imported Indian films (1936 onwards). Indian classical music was introduced to the island in 1966, but is not performed in Felicity.Musical change in Felicity since the beginning of the 20th century has followed a pattern of revitalization whereby older Bhojpuri forms in oral tradition are gradually forgotten and newly introduced Hindi forms are adopted by the community. The spoken language in Felicity is now English (Bhojpuri is used only by the older generation); consequently, the difficulty of song texts is an important consideration in the evolution of the musical repertory of the village. In 1974-75, a new repertory of songs devoted to the Hindu saint, Satya Sai Baba, was introduced to the village and adopted in one of the temples. The Sai Baba songs with their simple one- or two-line Hindi texts are easy to learn; their style, characterized by accelerando and loud handclapping, makes them an effective expression for East Indian feelings of ethnic solidarity