Anomaly detection has extensive use in a wide variety of applications, such techniques aim to and patterns in data that do not conform to expected behavior. In this work we apply anomaly detection to the task of discovering anomalies from user-generated content of commercial product descriptions. While most of the other works in literature rely exclusively on textual features, we combine those ...

In this paper, we propose a system that automatically generates templates for detecting Chinese character errors. We first collect the confusion sets for each high-frequency Chinese character. Error types include pronunciation-related errors and radical-related errors. With the help of the confusion sets, our system generates possible error patterns in context, which will be used as detection t...

This paper presents a system for the detection and correction of syntactic errors. It combines a robust morphosyntactic analyser and two groups of finite-state transducers specified using the Xerox Finite State Tool (XFST). One of the groups is used for the description of syntactic error patterns while the second one is used for the correction of the detected errors. The system has been tested ...

Existing methods for text detection in images are simple: most of them are based on texture estimation or edge detection followed by an accumulation of these characteristics. Geometrical constraints are enforced by most of the methods. However, it is done in a morphological post-processing step only. It is obvious, that a weak detection is very difficult — up to impossible — to correct in a pos...

This paper proposes an algorithm for detecting artificial text in video frames using edge information. First, an edge map is created using the Canny edge detector. Then, morphological dilation and opening are used in order to connect the vertical edges and eliminate false alarms. Bounding boxes are determined for every non-zero valued connected component, consisting the initial candidate text a...

This work uses the L-system to construct a tree structure for the text sequence and derives its complexity [1]. It serves as a measure of structural complexity of the text. It is applied to anomaly detection in data transmission. Keyword: text complexity, anomaly detection, structural complexity, rewriting rule, context-free grammar, L-system

Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test which remove detections that are not likely to ...

Abstract— Text data present in images and video contain useful information for automatic annotation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image...

Design of a new intelligent driver assistance system based on traffic sign detection with Persian context is concerned in this paper. The primary aim of this system is to increase the precision of drivers in choosing their path with regard to traffic signs. To achieve this goal, a new framework that implements fuzzy logic was used to detect traffic signs in videos captured along a highway f...

Text emotion detection refers to identifying the type of emotion getting used by the text. The process involves two process training and testing. The training section involves training the classifier with the text and the testing section involves the identification of the type of text used. After this accuracy of the classifier is checked by measuring how many correct labels of the text does th...