This paper propose a method of writer verification based on on-line features extracted from a process of drawing a figure, and evaluate its performance on handdrawn figures by genuine writers and pretenders. In the proposed method, a person in registration writes only the reference figure, which is composed of as many parts as possible and the person can be verified with a arbitrary part of the reference figure. The verification is based on a spotting method called CDP (Continuous Dynamic Programming). From some requirements in authentication system, the proposed method is tested through some experiments using figures. The error rates in the experiment were different depending on conditions such as kind of on-line features, minimum number of strokes comprised in acceptable test sequence as input, figure for determination of threshold and the genuine writer. The result of the experiment shows that the proposed method is effective.

This paper summarizes the research activities of the pastdecade on the recognition of handwritten scripts used inChina, Japan, and Korea. It presents the recognitionmethodologies, features explored, databases used, andclassification schemes investigated. In addition, it includes adescription of the performance of numerous recognitionsystems found in both academic and industrial researchlaboratories. Recent achievements and applications are alsopresented. A list of relevant references is attached togetherwith our remarks on this subject.

A feasibility experiment on an automatic signature verification system based on writing pressure was conducted using a new device sensing the z-axis component of writing pressure. The data acquisitions were conducted over a half a year for checking both subjects' and device stabilities. The DP (dynamic programming) matching method provided 6% error rates for type I and type II errors. The nature of signature writing pressure was investigated.

A new type of mobile platform with a novel wheel mechanism for holonomic and omnidirectional robots is presented. The drive mechanism equips with a couple of standard wheels in a differential-drive manner driven by two independent motors. A steering joint, driven by the third motor, is mounted on the differential drive mechanism at a location off-centered from a mid-point of the two wheels. Thus, the drive mechanism has a dual-wheel-caster configuration. First, the concept of the original caster drive is reviewed briefly followed by kinematic analysis of the dual-wheel-caster mechanism. A prototype vehicle is designed, built and its mobility tested. Other possible variation for the future vehicle design with a traditional synchro-drive mechanism is proposed. The kinematics and statics of the drive mechanism are also analyzed. All wheel driving without over constraint decoupled control and efficient driving can be achieved with the proposed synchro-drive.

This paper includes a description of 3 affiliated oriental languages: Chinese, Japanese, and Korean. It includes a description of the origins of these 3 languages and the inter-relationship among them. Drawn from the viewpoints of several experienced researchers in the field of OCR (Optical Character Recognition) and computational linguistics, it attempts to bring out the intriguing aspects of these 3 ideographic languages, including the formation and composition of pictograms, special features, learning, understanding, contextual information, and recognition of characters and words, and their relations to poetic expressions and pattern recognition techniques. Numerous references are given and comments on future trends are also presented.

A new type of holonomic omnidirectional vehicle which consists of wheel mechanisms without free rollers but with conventional tires is presented. We first present the concept of a new driving wheel mechanism with a tire in the conventional style such as a rubber tire or a pneumatic tire, an "offset steered driving wheel". The configuration of the wheel has an offset distance between the wheel axle and the steering axle along the direction of wheel travelling. We then describe the kinematics and the control method of the offset steered driving wheel to provide an omnidirectional and holonomic capability for a vehicle by actuating the wheel axis and the steering axis independently. The wheel is a nonholonomic system, and we introduce a control strategy to avoid a nonholonomic constraint. Simulation results of the single driving wheel and the two-wheeled vehicle are performed to test the control method. The concept of offset steered driving wheel is implemented and tested on a prototype of the holonomic omnidirectional vehicle. Experimental results demonstrate high mobility of the vehicle prototype.

An omnidirectional holonomic mobile robot assembled with nonholonomic wheels has been proposed. The driving wheel axis of the nonholonomic wheel has an offset distance from the steering axis of the wheel. A wheel of this style is representative of the nonholonomic system and is conventionally used for a caster wheel. In the case of the proposed mobile robot, a wheel of this style is used as a driven wheel by actuating a wheel axle and a steering axle independently. First, we describe the modeling and control of the single nonholonomic wheel, and then describe the holonomic vehicle which has a couple of these nonholonomic wheels. To avoid the nonholonomic characteristics of the wheel, we have introduced a control method which restricts the controlled statement to only the translational velocity of the supporting point of the wheel. Computer simulations of the single wheel and of the two wheeled vehicle, and experimental results of the single wheel have shown good performances.

Recognition of handwritten character strings is a challenging problem, because we need to cope with variations of shapes and touching/breaking of characters at the same time. A natural approach to recognizing such complex objects is as follows: The object is decomposed into segments, and meaningful partial shapes (shapes which are recognized as some characters) are constructed by merging segments locally. Then, a globally consistent interpretation of the object is determined from the combination of partial shapes. This approach can be referred to as a model-based split-and-merge method. Based on this idea, we present an algorithm for recognition and segmentation of character strings. We give systematic performance statistics by experiments using handwritten numerals. This algorithm can be applied to character strings composed of any number of characters and any type of touching or breaking, whether the number of constituent characters is known or unknown.

Proposes a simple and effective scheme to combine different algorithms, called a recognition filter. This scheme requires a strong restriction to each algorithm on substitution rates and recognition speed. To satisfy this restriction, we used a decision-tree frame with model-based restriction. The number of substitution errors of the algorithm was zero for about 13,000 handwritten numerals which had been used to construct the tree. For about 143,000 other data sets, the number of errors was only 16, and all these can be considered as permissible ones or rather humans' mistakes. The recognition speed is about 250 cps on a SPARC IPX, at 28.5 MIPS. This algorithm also has the property that every revision improves the performance without side effects. This algorithm was combined with another OCR algorithm. then, the recognition speed became about 3 times faster and both recognition rates and substitution rates were improved as compared to the latter algorithm alone.>

In this paper, we propose the Cross Section Sequence Graph which describes line images in a simple and well structured form. It is composed of regular regions called cross section sequences and singular regions. A cross section sequence is a sequence of cross sections, each of which is constructed as a pair of boundary points almost perpendicular to the direction of the line. The sequence corresponds to a straight or curved line segment. The remaining regions are extracted as singular regions, each of which corresponds to an end point region, corner, branch, cross, and so on. The cross section sequence graph is useful for many kinds of feature extraction, especially for skeletonization since a singular region can be analyzed from adjacent regular regions. Experimental results show that the skeleton extracted from the cross section sequence graph is better than that of a pixel-wise skeletonization (thinning) in terms of both processing speed and the quality of the skeleton.

We present algebraic approach to the inductive learning of structural models and automatic construction of shape prototypes for character recognition on the basis of the algebraic description of curve structure proposed by Nishida and Mori (1991, 1992). A class in the structural models is a set of shapes that can be transformed continuously to each other. We consider an algebraic representation of continuous transformation of components of the shape, and give specific properties satisfied by each component in the class. The generalization rules in the inductive learning are specified from the viewpoints of continuous transformation of components and relational structure among the components. The learning procedure generalizes a pair of classes into one class incrementally and hierarchically in terms of the generalization rules. We show experimental results on handwritten numerals.>

The authors propose a compact and concise method of describing curves in terms of the quasi-topological features and the structure of each singular point. The quasi-topological features are the convexity, loop, and connectivity. The quasi-topological structure is analyzed in a hierarchical way, and algebraic structure is presented explicitly for each representation level. The lower-level representations are integrated into the higher-level one in a systematic way. When a curve has singular points (branch points), the curve is decomposed into components, where each is a simple arc or a simple closed curve, by decomposing each singular point. The description scheme is applied to character recognition.>

Research and development of OCR systems are considered from a historical point of view. The historical development of commercial systems is included. Both template matching and structure analysis approaches to R&D are considered. It is noted that the two approaches are coming closer and tending to merge. Commercial products are divided into three generations, for each of which some representative OCR systems are chosen and described in some detail. Some comments are made on recent techniques applied to OCR, such as expert systems and neural networks, and some open problems are indicated. The authors' views and hopes regarding future trends are presented.>

Machine recognition of handprinted Chinese characters has recently become very active in Japan. Both from the practical and the academic point of view, very encouraging results are reported. The work is described systematically and analyzed in terms of so-called feature matching, which is likely to be the mainstream of the research and development of machine recognition of handprinted Chinese characters. A database, ETL8 (881 Kanji, 71 hirakana, and 160 variations for each category), is explained, on which many experiments were performed. Recognition rates reported using this database can be compared, and so somewhat qualitative evaluation of these methods is described. Based on the comparative study, the merits and demerits of both feature and structural matching are discussed and some future directions are mentioned.

Textural features corresponding to human visual perception are very useful for optimum feature selection and texture analyzer design. We approximated in computational form six basic textural features, namely, coarseness, contrast, directionality, line-likeness, regularity, and roughness. In comparison with psychological measurements for human subjects, the computational measures gave good correspondences in rank correlation of 16 typical texture patterns. Similarity measurements using these features were attempted. The discrepancies between human vision and computerized techniques that we encountered in this study indicate fundamental problems in digital analysis of textures. Some of them could be overcome by analyzing their causes and using more sophisticated techniques.