MMFO: modified moth flame optimization algorithm for region based RGB color image segmentation

RGB Histogram based Color Image Segmentation Using Firefly Algorithm

In this paper, optimal multi-level image segmentation is proposed using the Firefly Algorithm (FA). In this work, RGB histogram of the image is considered for bi-level and multi-level segmentation. Optimal thresholds for each colour component are attained by maximizing Otsu’s between-class variance function. The proposed segmentation procedure is demonstrated using standard RGB dataset and vali...

Modified CLPSO-based fuzzy classification System: Color Image Segmentation

Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...

Color Image Segmentation to the RGB and HSI Model Based on Region Growing Algorithm

Image segmentation is to divide the image into disjoint homogenous regions or classes, where all the pixels in the same class must have some common characteristics. In this paper, a new algorithm proposed to segment regions in an image, which is based on determining seed regions in an image. The algorithm applied on images of different complexity. The segmentation applied on each band of the RG...

Clustering Based Region Growing Algorithm for Color Image Segmentation

We propose an image segmentation method based on combining unsupervised clustering in the color space with region growing in the image space. No ‘a priori’ knowledge is required about the number of regions in the image. The algorithm is useful for marker extraction or complete segmentation of multidimensional, and in particular color, images. The running time depends mostly upon the speed of th...

Image Segmentation Using RGB Decomposition and Modified Bacterial Foraging Optimization