Feature Extraction in Content-Based Image Retrieval

In recent decades, the increased usage and availability of digital cameras has created a vast amount of new information captured in the form of digital images. These images have been given an unprecedented level of accessibility through the Internet and sharing in social media. It is difficult to represent these images using text descriptions due to the amount of labour required to annotate large collections and the occurrence of inconsistencies in annotations caused by the differing perceptions of the individual annotators. This makes searching images using text-based methods ineffective (Rui, Huang & Chang, 1999). New techniques in Content Based Image Retrieval (CBIR) are being developed to accommodate indexing and searching images using Feature Extraction. Feature extraction algorithms use the content of digital images to produce Feature Vectors, which represent the important details of an image in a concise form and allow for complex analysis of the source image. ... In this chapter, we examine the most common features for indexing and searching images. This provides an introduction to the concepts used in Feature Extraction. For further information on specific techniques and their implementations, refer to the Additional Reading section.