Segmentation And Classification of Ct Cervix Images Using Bag of Visual Word Classifier

Abstract

Image processing is used in the medical field for detection of tumor. Image segmentation is a
vital part of image processing. Segmentation is the process of partitioning an image into
distinct regions. The algorithm has the steps of preprocessing, cervix extraction, cervix
boundary correction, image segmentation, feature extraction and image classification. The
image is preprocessed using Adaptive median filtering and Fuzzy thresholding. The cervix is
extracted using canny edge detection and border tracing algorithm. The cervix boundary
correction is performed using Adaptive Concave Hull algorithm. Segmentation is performed
using Region growing based technique. Then for the segmented tumor region, the features
are extracted using the GLCM (Gray Level Co-occurrence Matrix) algorithm. From the
features extracted, the image is classified as the benign or malignant cervix by using the
BOVW (Bag of Visual Word) classifier.