In this paper, we present a hierarchical self-organiziuig map applying to scaling and rotation invariant recognition of a 256 x 256-pixel color-texture image. Since Kohonen's Self-Organizing Mapping is not embedded with the invariant a-bility, some learning modifications are added in Rotarion and Scaling Invariant Selforganizing Map (RSISOM). The concept of hierarchy self-organiziing map, furthermore, is developed to improve the performance of RSISOIvI for a color image recognition. In the experiment, the proposed algorithm shows the efficient invariant capability under s-c&g and rotation as well as the distinguish capability in different color-texture images. Furthermore, the computa-tional time after applying the concept of Hiera...
Image segmentation means separation process that can divide the original image into smaller area wit...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
International audienceOne big challenge in computer vision is to extract robust and discriminative l...
Artificial neural networks have gained a lot of interest as empirical models for their powerful repr...
Abstract:- In this paper, a color segmentation algorithm is presented and the parameters are discuss...
Usually, the segmentation of color images is performed using cluster-based methods and the RGB space...
Color quantization (CQ) is an image processing task popularly used to convert true color images to p...
View references (12) Identification and recognition of objects in digital images is a fundamental t...
We propose a local texture descriptor based on a pyramidal composition of Self Organizing Map (SOM)....
[[abstract]]© 1999 World Scientific and Engineering Academy and Society-In this paper, a color segme...
In this paper the basic principles and developments of an unsupervised learning algorithm, the Self-...
We propose a two-stage hierarchical artificial neural network for the segmentation of color images b...
This paper proposes a new invariant feature-space system based in the log-polar image representation...
Segmentation of gray level images into regions of uniform texture is investigated. An unsupervised a...
Abstract — Color image segmentation using Kohonen Self-Organizing Map (SOM), is proposed in this stu...
Image segmentation means separation process that can divide the original image into smaller area wit...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
International audienceOne big challenge in computer vision is to extract robust and discriminative l...
Artificial neural networks have gained a lot of interest as empirical models for their powerful repr...
Abstract:- In this paper, a color segmentation algorithm is presented and the parameters are discuss...
Usually, the segmentation of color images is performed using cluster-based methods and the RGB space...
Color quantization (CQ) is an image processing task popularly used to convert true color images to p...
View references (12) Identification and recognition of objects in digital images is a fundamental t...
We propose a local texture descriptor based on a pyramidal composition of Self Organizing Map (SOM)....
[[abstract]]© 1999 World Scientific and Engineering Academy and Society-In this paper, a color segme...
In this paper the basic principles and developments of an unsupervised learning algorithm, the Self-...
We propose a two-stage hierarchical artificial neural network for the segmentation of color images b...
This paper proposes a new invariant feature-space system based in the log-polar image representation...
Segmentation of gray level images into regions of uniform texture is investigated. An unsupervised a...
Abstract — Color image segmentation using Kohonen Self-Organizing Map (SOM), is proposed in this stu...
Image segmentation means separation process that can divide the original image into smaller area wit...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
International audienceOne big challenge in computer vision is to extract robust and discriminative l...
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