Foreign Body Shape Classification Using Intuitionistic Fuzzy Rule Based Approach on Pediatric Radiography Images

Abstract

Segmentation is the significant key stage in image analysis towards partitioning an image into different regions which have homogeneous features such as color, shape, and texture which is very important in classifying different region shapes in an image. In general, images are considered fuzzy due to the uncertainty present in terms of vagueness. The regions contain imprecise gray levels and uncertain data values which makes the task of defining the membership function difficult due to lack of precise knowledge. The intuitionistic fuzzy rule-based shape classification approach is used to classify the different shapes, such as circular, polygon, sharp, and irregular of the aspired foreign body on pediatric radiography images. Experimental results show the effectiveness of the proposed method in contrast to conventional fuzzy rule base algorithm.