Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation
نویسندگان
چکیده
منابع مشابه
A Genetic Algorithm for Color Image Segmentation
A genetic algorithm for color image segmentation is proposed. The method represents an image as a weighted undirected graph, where nodes correspond to pixels, and edges connect similar pixels. Similarity between two pixels is computed by taking into account not only brightness, but also color and texture content. Experiments on images from the Berkeley Image Segmentation Dataset show that the m...
متن کاملA New Method for Color Gamut Mapping by Genetic Algorithm
To reproduce an image, it is necessary to map out of gamut colors of the image to destination gamut. It is clear that the best color gamut mapping introduces the perceptually closest image to the original one. In this study, a new color gamut mapping is purposed by the aid of Genetic Algorithm (GA). The color difference between the original and mapped images based on S-LAB formula was chosen as...
متن کاملColor Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the...
متن کاملColor Image Quantization Algorithm Based on Differential Evolution
Some stochastic optimization methods, such as Particle Swarm Optimization Algorithms (PSO) and Genetic Algorithms (GA), have been used to solve the color image quantization. Differential Evolution Algorithm (DE) is one of the powerful stochastic optimization methods. Few researches have been done for using DE to solve the color image quantization. This paper proposes a DE-based color image quan...
متن کاملColor Image Segmentation with Genetic Algorithm for In-field Weed Sensing
This study was undertaken to develop machine vision-based weed detection technology for outdoor natural lighting conditions. Supervised color image segmentation using a binary-coded genetic algorithm (GA) identifying a region in Hue-Saturation-Intensity (HSI) color space (GAHSI) for outdoor field weed sensing was successfully implemented. Images from two extreme intensity lighting conditions, t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Engineering, Technology & Applied Science Research
سال: 2016
ISSN: 1792-8036,2241-4487
DOI: 10.48084/etasr.799