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On-screen text is a rich information resource to query events in soccer video due to its close relation to what happens on the screen. However, low resolution, clutter background, unknown font, size, color, etc. prevent the efforts of using this resource for querying. This paper presents a novel approach for querying events in soccer video using on-screen texts. The proposed approach is completely...
The general objective of the ICFHR 2010 Handwriting Segmentation Contest organized in the context of ICFHR 2010 conference was to use well established evaluation practices and procedures in order to record recent advances in off-line handwriting segmentation. Two new benchmarking datasets, one for text line and one for word segmentation, were created in order to test and compare recent algorithms...
We propose a full-text search technique for image-scanned documents that does not recognize individual characters. The system is as fast as a full-text search of machine-readable documents. Such a system is important when working with historical handwritten manuscripts. The proposed method works independently of differences in language and font because it uses a new pseudo-coding scheme based on the...
In this study, we investigate several methods for enhancing scanned mokkan images to aid archeologists and historians in the interpretation of mokkans. Mokkans are wooden tablets with handwritten characters used in 8th century Japan. Due to damages and natural deterioration, the interpretation of the text on mokkans is difficult even for archeologists and historians. The automatic interpretation of...
Large scale retrieval of handwritten documents has primarily been focused around searching a query text in the OCR'ed transcription of the document images, which provides a limited view of the complete search process. Recent research advances have led to a number of content based retrieval techniques which expand the search scope to document content level (i.e. image features, meta-information). Based...
Automatic transcription of historical documents is vital for the creation of digital libraries. In this paper we propose graph similarity features as a novel descriptor for handwriting recognition in historical documents based on Hidden Markov Models. Using a structural graph-based representation of text images, a sequence of graph similarity features is extracted by means of dissimilarity embedding...
One of the major issues in document image processing is the efficient creation of ground truth in order to be used for training and evaluation purposes. Since a large number of tools have to be trained and evaluated in realistic circumstances, we need to have a quick and low cost way to create the corresponding ground truth. Moreover, the specific need for having the correct text correlated with the...
An approach for the detection of decorative elements - such as initials and headlines - and text regions, focused on ancient manuscripts, is presented. Due to their age, ancient manuscripts suffer from degradation and staining as well as ink is faded-out over the time. Identifying decorative elements and text regions allows indexing a manuscript and serves as input for Optical Character Recognition...
In this study we describe a new approach to extract layout of unconstrained handwritten letters such as those sent by individuals to companies. The proposed model uses a hierarchical combination of Conditional Random Fields (CRFs) which gives access to various levels of the layout interpretation. The analysis proceeds by decreasing the resolution and increasing the abstraction of the document, starting...
Document image segmentation to text lines is a critical stage towards unconstrained handwritten document recognition. Although morphological operations proved to be effective in processing machine-printed documents for several issues, similar methods for unconstraint-handwritten documents lack accuracy. We propose an efficient method based on binary morphology for text-line segmentation in such documents...
Arbitrary orientation and sparse data content are common characteristics of torn document. To ensure accuracy and reliability in computer-based analysis, content-zone segmentation is required. In our previous work, we studied segmentation of handwritten and printed text. A questioned document-piece in the form of an office note, however, might also contain non-text data like logos, graphics, and pictures...
Text recognition in ancient documents poses specific challenges such as degradation and staining, fading out of ink, fluctuating text lines, superimposing of text-elements or varying layouts, amongst others. To cope with those challenges, a texture-based approach is proposed, which exploits the fact that different kinds of textures have distinct orientation distributions. The orientation information...
Due to the advancement of digital media, a large number of electronic books are digitized from old paper books through digital cameras or scanners. The scanned image often contains the distractions such as noises outside the page boundary, skewed pages, and irregular distributions of image illumination that may degrade the quality of scanned images. As for this paper, we propose an alternative algorithm...
The splitting of touching characters remains a challenge in over-segmentation, which is crucial to the performance of integrated segmentation-recognition of handwritten character strings. In this paper, we propose a new method based on contour analysis for touching character splitting in Chinese handwriting. To reliably locate splitting points on the contour of touching pattern, we pair upper and...
In this paper, we present a robust method for text detection in color scene image. The algorithm is based on edge detection and connected-component. In our framework, firstly, multi-scale edge detection is achieved by Canny operator and an adaptive thresholding binary method. Secondly, the filtered edges are classified by the classifier trained by SVM combing HOG, LBP and several statistical features,...
The world we live in is labeled extensively for the benefit of humans. Yet, to date, robots have made little use of human readable text as a resource. In this paper we aim to draw attention to text as a readily available source of semantic information in robotics by implementing a system which allows robots to read visible text in natural scene images and to use this knowledge to interpret the content...
A method is proposed to locate text in camera- captured guidepost images. Firstly, due to its advantage of smoothing the low contrast information, mean shift method is applied to remove some complex background. In order to improve the time efficiency, we modify the traditional mean shift method. Secondly, two stage features are used for the edge map of image to classify it into candidate text blocks...
In this paper, we propose two lossless compression techniques that represent a two dimensional Run-length Coding which can achieve high compression ratio. This method works by partitioning the block regions of the input image into rectangles instead of working by runs of adjacent pixels, so it is found to be more efficient than ID RLE Run-length Coding for transmitting texts and image. In the first...
In this paper, we present a novel approach for Arabic Text-Independent Writer Identification and Verification. Given that the handwriting of different people is often visually distinctive, we propose a global approach based on texture analysis, where each writer's handwriting is regarded as a different texture. This allows us to apply a texture classification method mainly based on a set of new proposed...
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