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Robust extraction of text from scene images is essential for successful scene text recognition. Scene images usually have nonuniform illumination, complex background, and text-like objects. In this paper, we propose a text extraction algorithm by combining the adaptive binarization and perceptual color clustering method. Adaptive binarization method can handle gradual illumination changes on character...
Text separation in natural scenes is a crucial step to recognize scene text. Since computational power in a mobile device is limited, current text extraction methods are impractical in real-time devices. We propose efficient text extraction methods by utilizing user's indication. When user simply indicates focus or draws the line on touch screen, the system can extract text in natural scenes efficiently...
In this paper, an automatic recognition system for wine label images is described. The system includes detection and extraction of text for the recognition for wine label images. It deals with impediments caused by different font styles and font sizes, as well as illumination changes and noise effects. Firstly, the text region is extracted by an edge-histogram, and the text is binarized by clustering...
Medical image annotation remains a challenging task. Many feature schemes have been experimented with limited success. In this paper, we propose to improve the image categorization prediction through the employment of better feature schemes assessed with feature analysis. A new edge descriptor based on the Canny detector is proposed along with modified MPEG-7 features. Some preliminary results are...
Double boundary text, also called outlined text, problem is presented when the text boundary has different color with background color and text stroke color. This problem, which frequently occurs in natural text of signboards, imposes another obstacle to the proper extraction of text information. In this paper, an efficient method is proposed based on well-known filling algorithms and characteristics...
This paper investigates hardcopy watermarking based on the embedding of transparent logos into documents. Grayscale logos are embedded into specific locations of the text document aiming communication over the print-and-scan (PS) channel. The authenticating message is encoded into the document by selecting the relative position of the logos. At the detector, the logo positions are estimated by correlation...
In a multi-script multi-lingual environment, a document may contain text lines in more than one script/language forms. It is necessary to identify different script regions of the document in order to feed the document to the OCRs of individual language. With this context, this paper proposes to develop a monothetic algorithmic model to identify and separate text lines Telugu, Hindi and English scripts...
Distortion always appears in document images while scanning thick bound volumes. There are two kinds of distortion for the scanned grayscale images, shadow appears at the volumes' spine area, and warping of the words occurs in the shadow. In this paper, a novel text boundary lines based method for efficient restoration of warped scanning Chinese document images is presented. We first detect on which...
With the development of information technology, the number of scanned images is increasing rapidly. There are many important texts in these images. In order to satisfy the need of images viewing, text identification and text retrieval, this paper presents an efficient method for text segmentation. Firstly, localizes the text blocks in scanned image. Secondly, according to its gray/color distribution,...
In this paper an automated information system is presented, that classifies scripts to corresponding writers using graphology. The methodology is based on the idea of creating a representative of each alphabet symbol in each script via proper fitting of all realizations of the specific symbol in it. The decision for writer identification is based on pair-wise comparisons of statistical quantities...
Texts appearing on compound image are usually classified into scene text and imposed text. Imposed text, like scripts in videos, slogans in advertisements and titles in magazine covers, contains important information. In this paper, a multistep compression method that could preserve imposed text quality in restored image is presented. The method separates imposed text from background and compresses...
In this paper, we develop an HMM-based sliding video text recognizer and present our results on Turkish broadcast news for the hearing impaired. We use well known speech recognition techniques to model and recognize sliding video text characters using a minimal amount of labeled data. Baseline system without any language modeling gives a word error rate of 2.2% on 138 minutes of test data. We then...
This paper describes an approach towards an orientation and skew detection for texts in scanned documents. Before using OCR systems to obtain character information from images, a preprocessing stage, comprising a number of adjustments, has to be performed in order to obtain accurate results. One important operation that has to be considered is the skew correction, or deskewing, of the image, a fault...
This paper discusses the history and current trends of video retrieval, focusing mainly on video segmentation, indexing and search. The objective is to share with the readers how much we have done so far as well as the current trends in the field. Unlike text documents, video contains dynamic information such as audio, motion (object and/or camera motions), etc. Thus, indexing videos for future search...
Information deficiency is a huge problem when researching on video indexing and retrieval. On the other hand, text in video frames implies lots of semantics inherently, and can provide supplemental but important information for video data processing. A smart approach for text detection, localization and extraction in video frames is presented in this paper. Here, block change rate (BCR for short)...
The extraction of textual content from colour documents of a graphical nature is a complicated task. The text can be rendered in any colour, size and orientation while the existence of complex background graphics with repetitive patterns can make its localization and segmentation extremely difficult. Here, we propose a new method for extracting textual content from such colour images that makes no...
A novel method for the segmentation of double-sided ancient document images suffering from bleed-through effect is presented. It takes advantage of the level set framework to provide a completely integrated process for the segmentation of the text along with the removal of the bleed-through interfering patterns. This process is driven by three forces: 1) a binarization force based on an adaptive global...
The recognition of handwritten characters, words, and text arouses great interest today. To develop the best working system is subject of many papers published. With this paper, methods to improve the performance of existing word recognition systems are discussed. The availability of a sufficient data sets for training and testing the system assumed, optimization algorithms are presented. The usage...
We propose a novel approach for text line segmentation based on adaptive local projection profiles. Our algorithm is suitable for degraded documents with text lines written in large skew. The main novelty of our approach is applying the local algorithm in an incremental manner that adapts to the skew of each text line as it progresses. The proposed approach achieves very accurate results on a set...
Automatic processing of images of steles is a challenging problem due to the variation in their structures and body text characteristics. In this paper, area Voronoi diagram is used to represent the neighborhood of connected components in stele images containing Nom characters. Body text region is then extracted from stele images by the selection of appropriate adjacent Voronoi regions based on the...
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