Text extraction and text line detection is the foundation of document image analysis. Since many years, a large number of text detection methods have been proposed, where these methods depend on convinced assumptions of documents with various font style, font size, distorted text, uneven lighting, complex background and low resolution. In this paper, reveals k-nearest neighbor rule as a generic...

Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content – based classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning. In this paper emotion recognition based on textual data and the techniques used in emo...

Detecting text regions in natural scenes is an important part of computer vision. We propose a novel text detection algorithm that extracts six different classes features of text, and uses Modest AdaBoost with multi-scale sequential search. Experiments show that our algorithm can detect text regions with a f= 0.70, from the ICDAR 2003 datasets which include images with text of various fonts, si...

The aim of text frame classification technique is to label a video frame as text or non-text before text detection and recognition. It is an essential step prior to text detection because text detection methods assume the input to be a text frame. Consequently, when a non-text frame is subjected to text detection, the precision of the text detection method decreases because of false positives. ...

The mounting escalation of multimedia content in information indexing and retrieval has made a high venture for extracting the text from videos. In this paper a new approach has been made using Stroke Width Transform (SWT) with intuitionistic fuzzy set theory for detecting text from images. The proposed methodology uses a fuzzy based edge detection method instead of the conventional edge detect...