Comprehensive Exploration of Image Segmentation: Methodologies, Implementations, and Foundational Insights
Abstract
Image segmentation is regarded as a fundamental process within the realm of image processing. It serves to decompose a digital image into distinct regions for analytical purposes. This process plays a critical role in the classification of objects within the image. Segmentation, essentially, reconfigures the image into a form that is more accessible for interpretation. In digital imagery, segmentation is predominantly utilized to delineate objects, boundaries, and other relevant features. Various methodologies can be employed for segmentation, including thresholding, clustering, and transformation techniques, among others. Upon the application of these methods, the resulting segmented image comprises a set of all individual pixels, each of which encapsulates distinct attributes such as texture, color, and other visual properties. This paper provides an extensive review of the literature from the past five years concerning the core techniques of image segmentation. DOI - https://doi.org/10.65525/SVUP.9788199565463.2026.56-67
Fields of Study & Subjects
Medical Image Segmentation Techniques
Advanced Neural Network Applications
Computer Science and Engineering
Publication details
- Pages
- 56–67
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Book chapter