Abstract Architectural drawings are an important source of information for many construction-related tasks, as they contain geometric and semantic about building parts. However, the manual extraction room stamps insertion such gleaned into facility management systems is quite laborious and, thus, its automation anticipated. In this paper, a method proposed to detect classify obscure or illegibl...

We present STE3D-CAP (pronounced as “steed-cap” /'stidkæp/), a text-based CAPTCHA that is built from stereoscopic 3D images. This is a completely new direction in CAPTCHA techniques. Our idea is to incorporate stereoscopic 3D images in order to present the CAPTCHA challenge in 3D, which will be easy for humans to read (as the text stands out in the 3D scene) but hard for computers. The main ide...

In this paper we describe a very simple and efficient method for the détection and recognition of the Malayalam text from colour natural scene images taken by a mobile phone camera. Malayalam text detection, skew correction of the detected text ,text segmentation and character recognition are the important steps in text understanding from natural scene images. Text understanding in natural scen...

In Text Information Extraction (TIE) process, the text regions are localized and extracted from the images. It is an active research problem in computer vision applications. Diversity in text is due to the differences in size, style, orientation, alignment of text, low image contrast and complex backgrounds. The semantic information provided by an image can be used in different applications suc...

We present a novel, flexible, statistical approach to modeling music, images and text jointly. The technique is based on multi-modal mixture models and efficient computation using online EM. The learned models can be used to browse multimedia databases, to query on a multimedia database using any combination of music, images and text (lyrics and other contextual information), to annotate docume...

We present a novel, flexible, statistical approach to modeling music, images and text jointly. The technique is based on multi-modal mixture models and efficient computation using online EM. The learned models can be used to browse multimedia databases, to query on a multimedia database using any combination of music, images and text (lyrics and other contextual information), to annotate docume...

We present a general method using kernel canonical correlation analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation and enables a comparison between the text and images. In the experiments, we look at two approaches of retrieving images based on only their content from a text query. We compare orthogonalization ...

This paper describes a dataset containing small images of text from everyday scenes. The purpose of the dataset is to support the development of new automated systems that can detect and analyze text. Although much research has been devoted to text detection and recognition in scanned documents, relatively little attention has been given to text detection in other types of images, such as photo...