This paper proposes a model-based structural matching method for handwritten Chinese character recognition (HCCR). This method is able to obtain reliable stroke correspondence and enable structural interpretation. In the model base, the reference character of each category is described in an attributed relational graph (ARG). The input character is described with feature points and line segment...

This paper presents writer-independent offline handwritten character recognition for Ethiopic script. The recognition is based on the characteristics of primitive strokes that make up characters. The spatial relationships of primitives whose combinations form complex structures of Ethiopic characters are used as a basis for recognition. Although this approach efficiently recognizes properly wri...

The Problem: In [3], we address the classic problem of handwritten character recognition. That is, given some classlabeled training examples of images of handwritten characters, identify the class of each of a set of test examples to the greatest possible accuracy. For example, when given a particular image of the character “8”, identify it as such. On isolated single character test images, suc...

Emotion recognition in microblogs like Twitter is the task of assigning an emotion to a post from a predefined set of labels. This is often performed based on the Tweet text. In this paper, we investigate wether information from attached images contributes to this classification task. We use o↵-the-shelf tools to extract a signal from an image. Firstly, with employ optical character recognition...

This paper proposes a new method to compare similarities of candidate models that are fitted to different areas of a query image. This method extracts the discriminant features that are changed due to the varying pose/lighting condition of given query image, and the confidence of each model-fitting is evaluated based on how much of the discriminant features is captured in each foreground. The c...

Researchers have thus far focused on the recognition of alpha and numeric characters in isolation as well as in context. In this paper we introduce a new genre of problems where the input pattern is taken to be a pair of characters. This adds to the complexity of the classi"cation task. The 10 class digit recognition problem is now transformed into a 100 class problem where the classes are M00,...

We present further work on evaluation of the fully automatic post-correction of Early Dutch Books Online, a collection of 10,333 18th century books. In prior work we evaluated the new implementation of Text-Induced Corpus Clean-up (TICCL) on the basis of a single book Gold Standard derived from this collection. In the current paper we revisit the same collection on the basis of a sizeable 1020 ...

The classification of digital documents is a complex task in a document analysis flow. The amount of documents resulting from the OCR retro-conversion (optical character recognition) makes the classification task harder. In the literature, different features are used to improve the classification quality. In this paper, we evaluate various features on OCRed and non OCRed documents. Thanks to th...

An essential stage in any text extraction system is the manual verification of the printed material converted by OCR. This proves to be the most labor-intensive step in the process. In a system built and deployed at the National Library of Medicine to automatically extract bibliographic data from scanned biomedical journals, alternative means were considered to validate the text. This paper des...