Given two handwritten documents, the writer verification problem is to determine whether the two documents were written by the same person. It is tackled by extracting various features and classi­ fying the patterns into their classes. Features are diverse in type while techniques in pattern recognition typically require that features be ho­ mogeneous. The solution proposed overcomes both the non­homogeneity of features and the intractability of infinite number of writers by a di­ chotomy transformation. In this model, the distance between each homogeneous feature type is used. We integrate several distance measures for many feature types: element, histogram, string, convex hull, etc into one useful for writer verification. Experimental results with 1

The design and functionality of a versatile search engine on handwritten documents is described. Documents are indexed using global image features, e.g., stroke width, slant, word gaps, as well local features that describe shapes of characters and words. Image indexing is done automatically using page analysis, page segmentation, line separation, word segmentation and recognition of characters and words. Several types of searches are

Document storage and retrieval capabilities of the CEDAR-FOX forensic handwritten document examination system are described. The system is designed for automated and semi-automated analysis of scanned handwritten documents. For library creation, the system provides functionalities for (i) entering document metadata, e.g., identification number, writer and other collateral information, (ii) creating a textual transcript of the image content at the word level, and (iii) including automatically extracted document level features, e.g, stroke width, slant, word gaps, as well as finer features that capture the structural characteristics of characters and words. For extracting these features the system performs page analysis, page segmentation, line separation, word segmentation and finally recognition of characters and words. The extracted features are used for writer identification by matching against a library built as a database. The system design is driven by questioned document examination with its emphasis on writer identification. Several query modalities are permitted for retrieval: (i) document level: the entire document image is the query; (ii) partial image: a region of interest (ROI) of a document; (ii) word image: which is also called word

Handwriting originates from a particular copybook style such as Palmer or Zaner-Bloser that one learns in childhood. Since questioned document examination plays an important investigative and forensic role in many types of crime, it is important to develop a system that helps objectively identify a questioned document’s handwriting style. Here, we propose a computer vision system that can assist a document examiner in the identification of a writer’s handwriting style and therefore the origin or nationality of an unknown writer of a questioned document. We collected 33 English alphabet copybook styles from 18 countries. Each character in a questioned document is segmented and matched against all of the 33 handwriting copybook styles. The more characters present in the questioned document, the higher the accuracy observed.

Since handwriting is influenced by physiology, training and other behavioral factors, a study of the handwriting of twins can shed light on the individuality of handwriting. The paper describes the methodology and results of such a study where handwriting samples of twins were compared by an automatic handwriting verification system. The results complement that of a previous study where a diverse population was used. The present study involves samples of 206 pairs of twins, where each sample consisted of a page of handwriting. The verification task was to determine whether two half-page documents (where the original samples were divided into upper and lower halves) were written by the same individual. For twins there were 1236 verification cases – including 824 tests where the textual content of writing was different and 412 tests where it was the same. An additional set of 1,648 test cases were obtained from handwriting samples of non-twins (general population). In order to make the handwriting comparison, the system computed macro features (overall pictorial attributes), micro features (characteristics of individual letters) , and style features (characteristics of whole-word shapes and letter pairs). Four testing scenarios were evaluated: twins and non-twins writing the same text and writing different texts. Results of the verification tests

A common forensic problem is determining the writer of a questioned document. Identifying the copybook style of a questioned document can help reduce the suspect population as an important step towards the identification of an individual writer. This feasibility study presents a method of identifying the copybook style of a questioned document using pseudo-online data and a string edit distance. In addition, clustering analysis performed on the database reveals similarities among the copybook styles. 1.

This paper explores whether features of structured writing can serve to discriminate users of handheld devices such as Palm PDAs. Biometric authentication would obviate the need to remember a password or to keep it secret, requiring only that a user’s manner of writing confirm his or her identity. Presumably, a user’s dynamic and invisible writing style would be difficult for an imposter to imitate. We show how handwritten, multi-character strings can serve as personalized, non-secret passwords. A prototype system employing support vector machine classifiers was built to discriminate 52 users in a closed-world scenario. On high-quality data, strings as short as four letters achieved a false-match rate of 0.04%, at a corresponding false non-match rate of 0.64%. Strings of at least 8 to 16 letters in length delivered perfect results—a 0 % equal-error rate. Very similar results were obtained upon decreasing the data quality or upon increasing the data quantity. 1.

Forensic document examination is at a cross-roads due to challenges posed to its scientific basis as well as due to the availability of revolutionary computer methods. This paper surveys recent efforts in the areas of establishing a scientific basis of forensic handwriting examination, software tools to assist document examiners and software systems that automate some of the examination process. This includes tools that compute features and provide visualization to assist the document examiner, verification methods to provide the degree of match between a questioned and known document, identification methods that narrow-down the search from a repository of documents with known writers, and software architectures that allow a variety of forensic tools to be integrated. I.