Arbitrary-shaped text detection has recently attracted increasing interests and witnessed rapid development with the popularity of deep learning algorithms. Nevertheless, existing approaches often obtain inaccurate results, mainly due to relatively weak ability utilize context information inappropriate choice offset references. This paper presents a novel instance expression which integrates bo...

Determining the direction of plagiarism (who plagiarized whom in a given pair of documents) is one of the most interesting problems in the field of automatic plagiarism detection. We present here an approach using an extension of the method Encoplot, which won the 1st international competition on plagiarism detection in 2009. We have tested it on a large-scale corpus of artificial plagiarism, w...

In this paper, we propose a refined scene text detector with a novel Feature Enhancement Network (FEN) for Region Proposal and Text Detection Refinement. Retrospectively, both region proposal with only 3 × 3 sliding-window feature and text detection refinement with single scale high level feature are insufficient, especially for smaller scene text. Therefore, we design a new FEN network with ta...

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...

We propose a text scanner, which detects wide text strings in a sequence of scene images. For scene text detection, we use a multiple-CAMShift algorithm on a text probability image produced by a multi-layer perceptron. To provide enhanced resolution of the extracted text images, we perform the text detection process after generating a mosaic image in a fast and robust image registration

Data quality is a critical aspect of applications that support business operations. Often entities are represented more than once in data repositories. Since duplicate records do not share a common key, they are hard to detect. Duplicate detection over text is usually performed using lexical approaches, which do not capture text sense. The difficulties increase when the duplicate detection must...

Embedded-Text Detection and Its Application to Anti-Spam Filtering Ching-Tung Wu Embedded-text in images usually carry important messages about the content. In the past, several algorithms have been proposed to detect text boxes in video frames. Previous work often followed a multi-step framework using a combination of image-analysis and machine-learning techniques. In this work, we propose a u...

The automatic detection of text within a natural image is an important problem in many applications. Text detection in natural images has gained much attention in the last years as it is a primary step towards fully autonomous text recognition. It needs to be fast, efficient and robust in order to feed an OCR classifier with the correct input. In other words, segmented regions must correspond t...

There are a variety of grand challenges for text extraction in scene videos by robots and users, e.g., heterogeneous background, varied text, nonuniform illumination, arbitrary motion and poor contrast. Most previous video text detection methods are investigated with local information, i.e., within individual frames, with limited performance. In this paper, we propose a unified tracking based t...