Text Extraction and Clustering for Multimedia: A review on Techniques and Challenges

Abstract

The internet technologies have developed rapidly over recent times producing massive sets of multimedia data where text, images, audios, and videos delivering a huge set of content. The text ingrained in this multimedia is generated from the web and social media that carry complex and meaningful data. There is an increasing need to recognize and extract text from multimedia data which is in unstructured form. Many new techniques have been applied to address the need for text extraction for multimedia but not all have been efficient. One important application of text analysis is to extract text information and then recognize meaningful data visualization for better decisions. This paper focuses on addressing significant text extraction and clustering structures, techniques and challenges from multimedia data set. We will highlight different approaches to text extraction and clustering from multimedia content.