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Optical Character Recognition (OCR) converts images of handwritten or printed text captured by camera or scanner into editable text. OCR has seen limited adoption in mobile platforms due to the performance constraints of these systems. Intel® Atom™ processors have enabled general purpose applications to be executed on handheld devices. In this paper, we analyze a reference implementation of the OCR...
In this paper, we define a new paradigm for eight-connection labeling, which employes a general approach to improve neighborhood exploration and minimizes the number of memory accesses. First, we exploit and extend the decision table formalism introducing or-decision tables, in which multiple alternative actions are managed. An automatic procedure to synthesize the optimal decision tree from the decision...
We report on the creation of a database composed of images of Arabic Printed words. The purpose of this database is the large-scale benchmarking of open-vocabulary, multi-font, multi-size and multi-style text recognition systems in Arabic. The challenges that are addressed by the database are in the variability of the sizes, fonts and style used to generate the images. A focus is also given on low-resolution...
This paper presents a graph based scheme for color text recognition in images and videos, which is particularly robust to complex background, low resolution or video coding artifacts. This scheme is based on a novel method named the image text recognition graph (iTRG) composed of five main modules: an image text segmentation module, a graph connection builder module, a character recognition module,...
We propose a combined character separation and recognition approach for low-resolution images of alphanumeric text. By synthesising the image formation process a set of low-resolution templates is created for each character. Cluster algorithms and normalised cross-correlation are then applied to match these templates and thereby allowing both character separation and recognition to be achieved at...
Current Web indexing technologies suffer from a severe drawback due to the fact that Web documents often present textual information that is encapsulated in digital images and therefore not available as actual coded text. Moreover such images are not suited to be processed by existing OCR software, since they are generally designed for recognizing binary document images produced by scanners with resolutions...
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