Contents 1 Background 4 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Types of handwriting recognition systems . . . . . . . . . . . . . . . . 5 1.2.1 Ooe-line recognition . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.2 On-line recognition . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.3 Character sets . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.4 Writing style variations . . . . . . . . . . . . . . . . . . . . . . 7 1.2.4.1 Variations of characters . . . . . . . . . . . . . . . . 7 1.2.4.2 Alignment of characters . . . . . . . . . . . . . . . . 8 1.2.4.3 Personal background factors . . . . . . . . . . . . . . 8 1.2.4.4 Situational factors . . . . . . . . . . . . . . . . . . . 9 1.2.4.5 Material factors . . . . . . . . . . . . . . . . . . . . . 9 1.2.4.6 Constraints on writing . . . . . . . . . . . . . . . . . 9 1.2.5 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.3 Beneøt

In this paper we give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using pen-based devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. The system provides a simple and easy way for users to verify the correctness of their handwritten expressions and, if needed, to correct any errors in recognition. Choosing mathematical operations is done making use of context menus, both with input and output expressions. Key words: PC-tablets, Pen-based input, Maple 1

In this paper we present two algorithms for handwritten digit classification based on the higher order singular value decomposition (HOSVD). The first algorithm uses HOSVD for construction of the class models and achieves classification results with error rate lower than 6%. The second algorithm uses the HOSVD for tensor approximation simultaneously in two modes. Classification results for the second algorithm are almost down at 5 % even though the approximation reduces the original training data with more than 98 % before the construction of the class models. The actual classification in the test phase for both algorithms is conducted by solving a series least squares problems. Considering computational amount for the test presented the second algorithm is twice as efficient as the first one.

It is widely believed that mathematics will be one of the major applications for Tablet PCs and other pen-based devices. In this paper we discuss many of the issues that make doing mathematics on such pen-based devices a hard task. We give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using penbased devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. The system provides a simple and easy way for users to verify the correctness of their handwritten expressions and, if needed, to correct any errors in recognition. Choosing mathematical operations is done making use of context menus, both with input and output expressions. Key words: PC-tablets, Pen-based math, Computer Algebra systems 1

this document.) Data points are collected as a time sequenced (x,y) points sampled along the stylus' trajectory. The program gathers these points and attempts to fit one of the two types of geometric primitives: (1) A straight line segment, or (2) An arc segment of a circle. We refer to this process as `segmentation '. Figure 5 shows an example. The figure on the left corresponds to the unprocessed ink as obtained directly from the digitizing tablet. The figure on the right shows the resulting symbol after segmentation