Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Detección automática de presencia/ausencia de atún en imágenes obtenidas mediante sonar de largo alcance a bordo de buques pesqueros y aplicación de Optical Character Recognition (OCR) para la extracción de parámetros

En esta tesis de máster se presenta una metodología para el análisis automatizado de las señales del sonar de largo alcance y una aplicación basada en la técnica de reconocimiento óptico de Optical Character Recognition, caracteres (OCR). La primera contribución consiste en el análisis de imágenes de sonar mediante técnicas de procesamiento de imágenes. En este proceso, para cada imagen de sonar se extraen y se analizan las regiones medibles, obteniendo para cada región un conjunto de características. Con la ayuda de los expertos, cada región es identi cada en una clase (atún o no-atún). De este modo, mediante el aprendizaje supervisado se genera la base de datos y, a su vez, se obtiene un modelo de clasi cación. La segunda contribución es una aplicación OCR que reconoce y extrae de las capturas de pantalla de imágenes de sonar, los caracteres alfanuméricos correspondientes a los parámetros de situación (velocidad, rumbo, localización GPS) y la confi guración de sonar (ganancias, inclinación, ancho del haz). El objetivo de este proceso es el de maximizar la e ficiencia en la detección de atún en el Golfo de Vizcaya y dar el primer paso hacia el desarrollo de un índice de abundancia de esta especie, el cual esté basado en el procesamiento automático de las imágenes de sonar grabadas a bordo de la ota pesquera durante su actividad pesquera rutinaria.

Trainable character recognition interface computer (INCOM) /

"UILU-ENG 78 1737."

On-line character recognition /

Bibliography: p. 14.

Offline Handwritten Malayalam Character Recognition Based on Chain Code Histogram

Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification

Developing Optical Character Recoginition for Ethiopic Scripts

The Amharic language is the Official language of over 70 million people mainly in Ethiopia. An extensive literature survey and the government report reveal no single Amharic character recognition is found in the country. The Amharic script has 33 basic characters each with seven orders giving 310 distinct characters, including numbers and punctuation symbols. The characters are visually similar; there is a typeface, but no capitalization. Beside this there is no any standard font to use the language in the computer but they use different fonts developed by different stakeholders without keeping a standard on their own way and interest and this create a problem of incompatibility between different fonts and documents.This project is to investigate the reason why Amharic optical character recognition is not addressed by local and international researchers and developers and finally to develop Amharic optical character recognition uses the features and facilities of Microsoft windows Vista or 7 using Unicode standard.

Model-based character recognition in low resolution

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 the same time. Thus characters are recognised using their low-resolution appearance only without applying image enhancement methods. Experiments showed that this approach is able to recognise low-resolution alphanumeric text of down to 5 pixels in size.

Optical scanning technology for purposes other than ballot counting /

Mode of access: Internet.

NORMAN (NORMalizing ANalyzer) /

Thesis (M.S.)--University of Illinois.