Auto Secured Text Monitor in Natural Scene Images

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 4

Abstract

Abstract: Monitoring the text in content based images is an important task. An accurate and robust method to monitor texts in natural scene images. In this paper fast and effective decision tree algorithm (MSERs) is used to extract a character participant by reducing regularized character dissimilarities. Character participant are grouped into text participant by using single-link clustering algorithm. Text participant with high non-text probabilities are removed and texts are establish with a text classifier. Valuable information may be broken in many content-based images, such as web images. We need to detect text before recognizing and retrieving.

Authors and Affiliations

Sowmya H N , Swetha Dareshwar , Sowmya K , Vijayalakshmi S Katti , Sushitha S , N. Samanvita

Keywords

Related Articles

 Segmentation to Sound Conversion

 Abstract: Our motive, the task of unsupervised topic segmentation of speech data operating over raw acoustic information. In contrast to existing algorithms for topic segmentation of speech, our approach does not r...

 An Extended Approach for Online Testing of Reversible Circuits

 Reversible computing has tremendous benefits in terms of power consumption, less heat dissipation and packaging density. Because its applications are found in diverse fields including quantum computing, nanotech...

 Data Security Model Enhancement In Cloud Environment

 Cloud computing is one of the most emerging technologies which plays an important role in the next generation architecture of IT Enterprise. It has been widely accepted due to its ability to reduce costs associat...

Novel Malware Clustering System Based on Kernel Data Structure

Abstract : An operating system kernel is the prime of system software, responsible for the integrity and conventional computer system’s operations. Traditional malware detection approaches have based on the codecentricas...

 Detection of Cancer in Pap smear Cytological Images Using Bag of Texture Features

 We present a visual dictionary based method for content based image retrieval in cervical microscopy images using texture features. The nucleus region in each image is identified by a simple and  reliable se...

Download PDF file
  • EP ID EP133646
  • DOI -
  • Views 106
  • Downloads 0

How To Cite

Sowmya H N, Swetha Dareshwar, Sowmya K, Vijayalakshmi S Katti, Sushitha S, N. Samanvita (2016). Auto Secured Text Monitor in Natural Scene Images. IOSR Journals (IOSR Journal of Computer Engineering), 18(4), 148-152. https://europub.co.uk/articles/-A-133646