Handwritten Signature Authentication Using Statistical Estimation

Supervised chromosome clustering and image classification

Abstract: In this paper we propose handwritten signature classification using a supervised chromosome clustering technique. Due to the time variant nature of handwriting of human being, a set of hundred sample handwritten signatures were first collected from the user or individual in form of the same sized grayscale images. These grayscale handwritten signature images will be used as the training set in our classification algorithm. Our proposed algorithm will then decide whether the future incoming handwritten signature of an individual can be a member of the training set or not. In this paper, the distance and similarities play an important role, where the greater the dissimilarity measure or distance of genes, the more dissimilar are the two chromosomes.

Effective Privacy-Preserving Iris Recognition

Abstract: The patterns of the structure of the irises are differed and unique to every single person. Any biometric authentication approach should consist of three requirements. They are non-invertibility, non-linkability, and revocability. By following feature transformation techniques, we propose an effective biometric recognition system for iris templates based on XOR function, while protecting the privacy of iris templates as well as above requirements. Compared to the other existing works, the recognition performances of the proposed approach are satisfactory. The final results of the research are fairly positive. The study opens for future enhancements.

Grayscale Image Classification Using Supervised Chromosome Clustering

Abstract: In this paper we propose Handwritten Signature Classification using supervised chromosome clustering technique. Due to the time variant nature of handwriting of human being, a set of hundred sample Handwritten Signatures first collected from the user or individual in form of same sized grayscale images. These grayscale handwritten signature images will be used as the training set in our classification algorithm. Our propose algorithm will then decide whether the future incoming handwritten signature of an individual can be a member of the training set or not. In this paper, distance and similarities play an important role, where the greater the dissimilarity measure or distance of genes, the more dissimilar are the two chromosomes.

Data hiding in binary image for authentication and annotation

Abstract: This paper proposes a new method to embed data in binary images, including scanned text, figures, and signatures. The method manipulates "flippable" pixels to enforce specific block-based relationship in order to embed a significant amount of data without causing noticeable artifacts. Shuffling is applied before embedding to equalize the uneven embedding capacity from region to region. The hidden data can be extracted without using the original image, and can also be accurately extracted after high quality printing and scanning with the help of a few registration marks. The proposed data embedding method can be used to detect unauthorized use of a digitized signature, and annotate or authenticate binary documents. The paper also presents analysis and discussions on robustness and security issues.

Image authentication techniques for surveillance applications

Abstract: In automatic video surveillance (VS) systems, the issue of authenticating the video content is of primary importance. Given the ease with which digital images and videos can be manipulated, practically they do not have any value as legal proof, if the possibility of authenticating their content is not provided. In this paper, the problem of authenticating video surveillance image sequences is considered. After an introduction motivating the need for a watermarking-based authentication of VS sequences, a brief survey of the main watermarking-based authentication techniques is presented and the requirements that an authentication algorithm should satisfy for VS applications, are discussed. A novel algorithm which is suitable for VS visual data authentication is also presented and the results obtained by applying it to test data are discussed.

Web based image authentication using invisible Fragile watermark

Abstract: The demand of security is getting higher in these days due to easy reproduction of digitally created multimedia data. Digital watermark is the emerging technique to embed secret information into content for copyright protection and authentication. Watermark is embedded within an image that alteration and modification to the watermarked image can be detected in a fragile watermark system. Watermark detection is blind that does not require an original image and it is invisible to avoid revealing secret information to malicious attackers. A web based image authentication method based in digital watermarking is described in this paper. It can provide more controls to image owners and conveniences to clients who want to get authenticity of image by integrating benefits of using Internet to the watermark system.

Data Embedding Based on Better Use of Bits in Image Pixels

Abstract: In this study, a novel approach of image embedding is introduced. The proposed method consists of three main steps. First, the edge of the image is detected using Sobel mask filters. Second, the least significant bit LSB of each pixel is used. Finally, a gray level connectivity is applied using a fuzzy approach and the ASCII code is used for information hiding. The prior bit of the LSB represents the edged image after gray level connectivity, and the remaining six bits represent the original image with very little difference in contrast. The proposed method embeds three images in one image and includes, as a special case of data embedding, information hiding, identifying and authenticating text embedded within the digital images. Image embedding method is considered to be one of the good compression methods, in terms of reserving memory space. Moreover, information hiding within digital image can be used for security information transfer. The creation and extraction of three embedded images, and hiding text information is discussed and illustrated, in the following sections. Keywords—Image embedding, Edge detection, gray level connectivity, information hiding, digital image compression.

Handwritten Digit Recognition: A Neural Network Demo

Abstract: A handwritten digit recognition system was used in a demonstration project to visualize artificial neural networks, in particular Kohonen's self-organizing feature map. The purpose of this project was to introduce neural networks through a relatively easy-to-understand application to the general public. This paper describes several techniques used for preprocessing the handwritten digits, as well as a number of ways in which neural networks were used for the recognition task. Whereas the main goal was a purely educational one, a moderate recognition rate of 98% was reached on a test set.