Fish detection using morphological approach based-on k-means segmentation

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Infected Fruit Part Detection using K-Means Clustering Segmentation Technique

— Nowadays, overseas commerce has increased drastically in many countries. Plenty fruits are imported from the other nations such as oranges, apples etc. Manual identification of defected fruit is very time consuming. This work presents a novel defect segmentation of fruits based on color features with K-means clustering unsupervised algorithm. We used color images of fruits for defect segmenta...

Optimization Fusion Approach For Image Segmentation Using K-Means Algorithm

This paper presents a new ,simple and Efficient segmentation approach,based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable, accurate and a non-overlapped image result. The main objective of the paper is to get a non-overlapping and a reliable output by using k-means and genetic algorithm. The...

Optimization Fusion Approach for Image Segmentation Using K-Means Algorithm

This paper presents a new, simple and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable, accurate and a non-overlapped image result. The main objective of the paper is to get a non-overlapping and a reliable output by using k-means and genetic algorithm. Th...

Morphological Image Processing Approach Using K-Means Clustering for Detection of Tumor in Brain

The brain is the anterior part of the central nervous system. Along with the spinal cord, it forms the central nervous system (CNS). Brain tumor is an abnormal growth caused by cells reproducing themselves in an uncontrolled manner. Magnetic resonance imaging (MRI) is the commonly used technique for diagnosis of brain tumors. In MRI, the amount of data obtained is very large to manually analyze...