A Survey on Handwritten Character Recognition using Machine Learning Technique

Due to its broad range of applications, handwritten character recognition is widespread. Processing application forms, digitizing ancient articles, processing postal addresses, processing bank checks, and many other handwritten character processing fields are increasing in popularity. Since the last three decades, handwritten characters have drawn the attention of researchers. For successful recognition, several methods have been suggested. This paper presents a comprehensive overview of handwritten character recognition using a neural network as a machine learning tool.

Off-line signature verification using elementary combinations of directional codes from boundary pixels

Verifying the genuineness of official documents, such as bank checks, certificates, contract forms, bonds, etc., remains a challenging task when it comes to accuracy and robustness. Here, the genuineness is related to the degree of match of the signature contained in the documents relating to the original signatures of the authorized person. Signatures of authorized persons are considered known in advance. In this paper, a novel feature set is introduced based on quasi-straightness of boundary pixel runs for signature verification. We extract the quasi-straight line segments using elementary combinations of the directional codes from the signature boundary pixels and subsequently we obtain the feature set from various quasi-straight line classes. The quasi-straight line segments provide a blending of straightness and small curvatures resulting in a robust feature set for the verification of signatures. We have used Support Vector Machine (SVM) for classification and have shown results on standard signature datasets like CEDAR (Center of Excellence for Document Analysis and Recognition) and GPDS-100 (Grupo de Procesado Digital de la Senal). The results establish how the proposed method outperforms the existing state of the art.

Arabic handwritten digits recognition based on convolutional neural networks with resnet-34 model

<span>Handwritten digits recognition has attracted the attention of researchers in pattern recognition fields, due to its importance in many applications in public real life, such as read bank checks and formal documents which is a continuous challenge in the last years. For this motivation, the researchers created several algorithms in recognition of different human languages, but the problem of the Arabic language is still widespread. Concerning its importance in many Arab and Islamic countries, because the people of these countries speak this language, However, there is still a little work to recognize patterns of letters and digits. In this paper, a new method is proposed that used pre-trained convolutional neural networks with resnet-34 model what is known as transfer learning for recognizing digits in the arabic language that provides us a high accuracy when this type of network is applied. This work uses a famous arabic handwritten digits dataset that called MADBase that contains 60000 training and 1000 testing samples that in later steps was converted to grayscale samples for convenient handling during the training process. This proposed method recorded the highest accuracy compared to previous methods, which is 99.6%.</span>

Tokenization of assets and products

This article is about tokenization of assets and products based on blockchain technology. Tokenization continues the idea of securities, but only in the field of digital technologies. Various financial instruments have long been used that eliminate the risks of turnover of valuable physical assets, such as precious metals, by replacing them with less valuable equivalents. This is, for example, the use of banknotes and coins made of non-precious metals, Bank checks, and so on. Tokenization allows you to convert rights to a valuable physical asset into a digital token. The objects of tokenization can be real estate, various securities, manufactured products or raw materials, and so on. Such a token can be put into circulation on primary and secondary markets, as well as, often, «cashed» – that is, it can be exchanged from the manufacturer for the corresponding products. An important feature of tokenization is the ability to divide the value of indivisible assets, such as art and collectibles. This allows you to attract investors with small capital and makes it easier to benefit from initially expensive and low-liquid assets. However, this technology has a number of problems. The main problem with tokenization is that there is still no clear regulation of these digital assets in all countries of the world. In the United States, for example, tokens are often equated with securities. In Germany, it is considered that each case of tokenization should be considered separately, but tokens that grant rights similar to those granted by traditional shares are classified as financial instruments and are subject to appropriate regulation. In the future, after the problems are resolved, tokenization can replace the traditional way of representing the value of physical assets – securities, and also become a convenient financial tool for trading products and assets.

Handwritten Text Recognition using Machine Learning Techniques in Application of NLP

Handwriting Detection is a technique or ability of a Computer to receive and interpret intelligible handwritten input from source such as paper documents, touch screen, photo graphs etc. Handwritten Text recognition is one of area pattern recognition. The purpose of pattern recognition is to categorizing or classification data or object of one of the classes or categories. Handwriting recognition is defined as the task of transforming a language represented in its spatial form of graphical marks into its symbolic representation. Each script has a set of icons, which are known as characters or letters, which have certain basic shapes. The goal of handwriting is to identify input characters or image correctly then analyzed to many automated process systems. This system will be applied to detect the writings of different format. The development of handwriting is more sophisticated, which is found various kinds of handwritten character such as digit, numeral, cursive script, symbols, and scripts including English and other languages. The automatic recognition of handwritten text can be extremely useful in many applications where it is necessary to process large volumes of handwritten data, such as recognition of addresses and postcodes on envelopes, interpretation of amounts on bank checks, document analysis, and verification of signatures. Therefore, computer is needed to be able to read document or data for ease of document processing.

Kewenangan Dan Ruang Lingkup Otoritas Jasa Keuangan Di Bidang Perbankan

The Financial Services Authority (OJK) is a financial service supervision institution such as the Banking Industry, Capital Market, Mutual Funds, Financing Companies, Pension Funds and Insurance. OJK has become an independent institution based on the Law Number 21 Year 2011 concerning OJK, which means it is free from intervention or interference from any party. The purpose of the establishment of OJK is that all activities in the Financial Services sector are carried out regularly, fairly, transparently and accountably; able to realize a financial system that grows in a sustainable and stable manner; and able to protect the interests of consumers and society.OJK has duties and authorities in the field of micropudential, which includes regulation and supervision of bank institutions, bank health, prudential aspects of banks, and bank checks. Whereas in the micropudential field, OJK's role is to assist Bank Indonesia (BI) to make moral appeals to the Banking Industry. Keywords: Financial Services Authority, Banking

KEWENANGAN OTORITAS JASA KEUANGAN DI BIDANG PERBANKAN DALAM MEWUJUDKAN KEPASTIAN HUKUM

National banking is one of the main pillars in national economic development, and is expected to be an agent of development in achieving national goals, so that required a strong and professional institutions in the regulation and supervision of the banking and independent of the intervention of other parties. discusses the authority of the Financial Services Authority in conducting banking regulatory and supervision in Indonesia with the principles of legal certainty, the relationship between the Financial Services Authority and Bank Indonesia in regulating and supervising the banking and OJK Independence in regulating and supervising banking in Indonesia. The research method used in this research is analytical descriptive research method, that is research which describe and describe various state or fact whic h exist about Authority of Financial Services Authority In Banking in Realizing Legal Certainty. Then the general description is analyzed by starting from the legislation, the existing theories and the opinions of experts who aims to find and get answers from the main issues that will be discussed further and using the method of normative juridical approach, namely research methods that emphasize the secondary data that is by studying and reviewing the principles of law and positive law rules derived from the existing literature materials in legislation and other legal provisions. The results of the research on the authority of the Financial Services Authority in the Banking Division in realizing legal certainty, Before the establishment of OJKyang perform the tasks and functions of regulation and supervision of banks is Bank Indonesia, but after the establishment of OJK, the tasks and functions of banking regulation and supervision turned to OJK. Between Bank Indonesia and OJK can not be separated there is still a connection. Bank Indonesia conducts Macroprudential Supervision, which regulates the stability of the financial system as a whole and comprehensively, while OJK conducts microprodential surveillance, namely Regulation and supervision on institutional, health, prudential aspects, and bank checks. But in its implementation does not close the possibility of overlapping. With the contribution or levy of companies conducting business activities in the financial services sector will affect the level of independence of OJK itself, so that the dues or charges should not be charged to the company, but charged to the state budget so that there is no conflict interest. Keywords: Bank Regulation & Supervision, Legal Certainty, OJK Independence

Fingerprint-Based Document Image Retrieval

Most of the documents use fingerprint impression for authentication. Property related documents, bank checks, application forms, etc., are the examples of such documents. Fingerprint-based document image retrieval system aims to provide a solution for searching and browsing of such digitized documents. The major challenges in implementing fingerprint-based document image retrieval are an efficient method for fingerprint detection and an effective feature extraction method. In this work, we propose a method for automatic detection of a fingerprint from given query document image employing Discrete Wavelet Transform (DWT)-based features and SVM classifier. In this paper, we also propose and investigate two feature extraction schemes, DWT and Stationary Wavelet Transform (SWT)-based Local Binary Pattern (LBP) features for fingerprint-based document image retrieval. The standardized Euclidean distance is employed for matching and ranking of the documents. Proposed method is tested on a database of 1200 document images and is also compared with current state-of-art. The proposed scheme provided 98.87% of detection accuracy and 73.08% of Mean Average Precision (MAP) for document image retrieval.