Text, Images, and Video Analytics for Fog Computing

Text, Images, and Video Analytics for Fog Computing

A. Jayanthiladevi (Jain University, India), S. Murugan (Mewer University, India) and K. Manivel (United Health Corporation, India)
DOI: 10.4018/978-1-5225-5972-6.ch018

Abstract

Today, images and image sequences (videos) make up about 80% of all corporate and public unstructured big data. As growth of unstructured data increases, analytical systems must assimilate and interpret images and videos as well as they interpret structured data such as text and numbers. An image is a set of signals sensed by the human eye and processed by the visual cortex in the brain creating a vivid experience of a scene that is instantly associated with concepts and objects previously perceived and recorded in one's memory. To a computer, images are either a raster image or a vector image. Simply put, raster images are a sequence of pixels with discreet numerical values for color; vector images are a set of color-annotated polygons. To perform analytics on images or videos, the geometric encoding must be transformed into constructs depicting physical features, objects and movement represented by the image or video. This chapter explores text, images, and video analytics in fog computing.
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Text Analytics

In the middle of 1980’s the text mining was evolved but it was not well developed due to lack of sophisticated technology. Later the technology developed and along with it, the text mining was also developed. In text analytics Most of all information or data is available in textual form in databases. From these contexts, manual Analytics or effective extraction of important information are not possible. For that it is relevant to provide some automatic tools for analyzing large textual data. Text analytics or text mining refers process of deriving important information from text data. It will use to extract meaningful data from the text in Dilpreet Kaur, (May- 2014) et al., Text analytics widely use in government, research, and business needs. Data simply tells that what people did but text analytics tell you why. The text analytics is also called as “text mining” and is a way that has the unstructured data.From unstructured or semi structured text data all information will retrieve. From all textual data it will extract important information. After extracting information it will be categorized.

Working in Text Mining

The text mining has many processes or working methods and all these are combined to obtain the results that are nothing but the working of text mining. The stages involved in it are shown in Figure 1.

Figure 1.

Text mining areas

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