most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. to solve the problem, this paper utilizes zernike moment (zm) and pseudo zernike moment (pzm) to extract object contour features in all situations such as rotation, scaling and shifting of object i...

Curvilinear text line detection and segmentation in handwritten documents is a significant challenge for handwriting recognition. Given no prior knowledge of script, we model text line detection as an image segmentation problem by enhancing text line structure using a Gaussian window, and adopting the level set method to evolve text line boundaries. Experiments show that the proposed method ach...

Text extraction and text line detection is the foundation of document image analysis. Since many years, a large number of text detection methods have been proposed, where these methods depend on convinced assumptions of documents with various font style, font size, distorted text, uneven lighting, complex background and low resolution. In this paper, reveals k-nearest neighbor rule as a generic...

in recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. detection of traffic signs is an effective method to reach the mentioned aims. in this paper a new intelligent driver assistance system based on traffic sig...

Document layout analysis is an important task needed for handwritten text recognition among other applications. Text layout commonly found in handwritten legacy documents is in the form of one or more paragraphs composed of parallel text lines. An approach for handwritten text line detection is presented which uses machinelearning techniques and methods widely used in natural language processin...

Text embedded in video sequences is very important to semantic indexing and content-based retrieval system, especially for large scale news collection. However, its detection and extraction is still an open problem due to the variety of its size and the complexity of the backgrounds. In this paper, we propose an approach for automatic Arabic-text localization based on a novel method for text-li...

Scene text reading continues to be of interest for many reasons including applications for the visually impaired and automatic image indexing systems. Here we propose a novel end-to-end scene text detection algorithm. First, for identifying text regions we design a novel Convolutional Neural Network (CNN) architecture that aggregates local surrounding information for cascaded, fast and accurate...

Document images produced by scanner or digital camera, usually suffer from geometric and photometric distortions. Both of them deteriorate the performance of OCR systems. In this paper, we present a novel method to compensate for undesirable geometric distortions aiming to improve OCR results. Our methodology is based on finding text lines by dynamic local connectivity map and then applying a l...