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...

Here we developed a MATLAB based Graphical User Interface for people to check the information of desired books in real-time. The GUI allows user to take photos of the book cover. Then it will automatically detect features of the input image based on MSER algorithm, then it will filter out non-text features based on morphological difference between text and non-text regions. In order to further ...

Psychology studies show that people detect deception no more accurately than by chance, and it is therefore important to develop tools to enable the detection of deception. The problem of deception detection has been studied for a significant amount of time, however in the last 1015 years we have seen methods of computational linguistics being employed with greater frequency. Texts are processe...

Passages can be hidden within a text to circumvent their disallowed transfer. Such release of compartmentalized information is of concern to all corporate and governmental organizations. Passage retrieval is well studied; we posit, however, that passage detection is not. Passage retrieval is the determination of the degree of relevance of blocks of text, namely passages, comprising a document. ...

The world wide web represents vast stores of information. However, the sheer amount of such information makes it practically impossible for any human user to be aware of much of it. Therefore, it would be very helpful to have a system that automatically discovers relevant, yet previously unknown information, and reports it to users in human-readable form. As the first attempt to accomplish such...

This thesis describes work on the detection of anomalous material in text without the use of training data. We use the term anomalous to refer to text that is irregular, or deviates significantly from its surrounding context. In this thesis we show that identifying such abnormalities in text can be viewed as a type of outlier detection because these anomalies will differ significantly from the ...

The problem of outlier detection is extremely challenging in many domains such as text, in which the attribute values are typically non-negative, and most values are zero. In such cases, it often becomes difficult to separate the outliers from the natural variations in the patterns in the underlying data. In this paper, we present a matrix factorization method, which is naturally able to distin...