In this paper, we propose a novel method for detecting and segmenting text layers in complex images. This method is robust against degradations such as shadows, non-uniform illumination, low-contrast, large signaldependent noise, smear and strain. The proposed method first uses a geodesic transform based on a morphological reconstruction technique to remove dark/light structures connected to th...

In this paper, we propose a novel method for detecting and segmenting text layers in complex images. This method is robust against degradations such as shadows, non-uniform illumination, low-contrast, large signaldependent noise, smear and strain. The proposed method first uses a geodesic transform based on a morphological reconstruction technique to remove dark/light structures connected to th...

We present a fast algorithm for Korean text extraction and segmentation from subway signboards using smart phone sensors in order to minimize computational time and memory usage. The algorithm can be used as preprocessing steps for optical character recognition (OCR): binarization, text location, and segmentation. An image of a signboard captured by smart phone camera while holding smart phone ...

Purpose To compare the agreement between optical coherence tomography (OCT)-based choroidal vascularity markers measured by two previously reported image binarization techniques. Methods Spectral-domain OCT using enhanced-depth imaging was performed in 100 eyes from 52 normal subjects. Choroidal images were binarized to luminal area and stromal area using two different algorithms. Choroidal v...

This paper presents an objective evaluation methodology for handwritten document image binarization techniques that aims to reduce the human involvement in the ground truth construction and consecutive testing. A detailed description of the methodology along with a benchmarking of the state-of-the-art binarization algorithms based on the proposed methodology is presented.

The document binarization of the degraded document is a challenging task due to variation in background and foreground. In recent years degraded documentation is active research topic. In this paper, the approach for segmentation of text from the degraded document images is presented by using adaptive image contrast. It is a combination of local image contrast and gradient. The performance of t...

In this paper, we propose a mechanism for systematic comparison of the efficacy of unsupervised evaluation methods for parameter selection of binarization algorithms in optical character recognition (OCR). We also analyze these measures statistically and ascertain whether a measure is suitable or not to assess a binarization method. The comparison process is streamlined in several steps. Given ...

Binarization is a well-known image processing task, whose objective to separate the foreground of an from background. One many tasks for which it useful that preprocessing document images in order identify relevant information, such as text or symbols. The wide variety types, alphabets, and formats makes binarization challenging. There are multiple proposals with solve this problem, classical m...