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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)...
Text detection in video images has received increasing attention, particularly in scene text detection in video images, as it plays a vital role in video indexing and information retrieval. This paper proposes a new and robust gradient difference technique for detecting both graphics and scene text in video images. The technique introduces the concept of zero crossing to determine the bounding boxes...
In this paper, we propose a new method based on wavelet transform, statistical features and central moments for both graphics and scene text detection in video images. The method uses wavelet single level decomposition LH, HL and HH subbands for computing features and the computed features are fed to k means clustering to classify the text pixel from the background of the image. The average of wavelet...
Text within a camera grabbed image can contain a huge amount of meta data about that scene. Such meta data can be useful for identification, indexing and retrieval purposes.Detection of colored scene text is a new challenge for all camera based images.Common problems for text extraction from camera based images are the lack of prior knowledge of any kind of text features such as color, font, size...
Information of text in videos and images plays an important role in semantic analysis. In this paper, we propose an effective method for text detection and localization in noisy background. The algorithm is based on corner response. Compared to non-text regions, there often exist dense edges and corners in text regions. So we can get relatively strong responses from text regions and low responses...
Text detection plays a vital role in retrieving and browsing video data efficiently and accurately. In this paper, we propose a method for detecting both graphics and scene text in video images by proposing initial text block identification, text portion segmentation and new edge features for false positive elimination. The heuristic rules based on filters and edge analysis are formed to identify...
Video text provides precise and meaningful information about video content. Video text extraction is a crucial step to retrieve video text characters. Most of papers perform video text extraction in a whole text row. Compared with whole text row extraction, single character extraction can achieve higher accuracy because the background of single character is relatively simple. However, character segmentation...
Texts presented in video can provide important semantic information. In this paper, we propose an algorithm to detect texts from news videos. First, SPAC (spatial autocorrelation method) is used to determine the degree of texture rough-detail of video frames and determine candidate text regions based on texture rough-detail. Then Sobel operator is used to extract edges of candidate text regions, and...
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. In this paper, we present a fast and robust approach for text detection, localization, extraction, and reorganization in video frames with complex background...
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