DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded
Today data mining has become a vital role in all fields. This is because they discover interesting patterns and relationship in a data repository. Data mining is suitable for various fields such as image processing, artificial intelligence, machine learning, statistics and computation capabilities. Image segmentation is the fundamental step in various image processing tasks such as image analysis, visualization, and object representation and so on. The goal of image segmentation is to simplify, to partition image into meaningful regions and easier to analyze. This paper presents an overview of various data mining techniques associated with image segmentation. The data mining techniques such as clustering, classification and association are very easy to implement image segmentation that delivers valuable results. The above techniques are helpful to retrieve information from the images that are used to diagnose diseases, face detection, to improve the segmentation quality and so on. This paper provides crispy report about the data mining techniques and how they fetch the information from the images.
