An Analysis of Image Segmentation Techniques for Image Processing Applications

Image processing techniques are a crucial component of modern computer technologies, playing a significant role in various applications such as the medical field, object detection, video surveillance systems, and computer vision. A key aspect of image processing is image segmentation, which involves dividing images into smaller parts known as segments. This process simplifies image representation to facilitate analysis. Numerous algorithms have been developed for image segmentation, each based on specific pixel features. This paper reviews and analyzes different segmentation algorithms, ultimately comparing them. Such a comparative study is valuable for enhancing the accuracy and performance of segmentation methods across various image processing domains.

Image Segmentation, Digital Image Processing, K-Means Clustering

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