COLOUR IMAGE RECOGNITION BASED ON SINGLE-LAYER NEURAL NETWORKS OF MIN/MAX NODES
COLOUR IMAGE RECOGNITION BASED ON SINGLE-LAYER NEURAL NETWORKS OF MIN/MAX NODES
复制标题
基于单层最小/最大节点神经网络的彩色图像识别
DOI：
10.14311/nnw.2012.22.024
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发表时间：
2012
影响因子：
0.8
通讯作者：
R. Holota
中科院分区：
文献类型：
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作者：
R. Holota
图像识别系统可以基于由最小/最大节点组成的单层神经网络。这个原理很容易用于灰度图像。然而，本文讨论了利用神经网络进行彩色图像识别的可能性。最近开发的软件演示和测试了几个原理。提出了一种适用于HSV （Hue Saturation Value）色彩空间识别的改进的最小/最大节点单层网络。
An image recognition system can be based on a single-layer neural network composed of Min/Max nodes. This principle is easy to use for greyscale images. However, this article deals with the possibilities of utilising neural nets for colour image recognition. Several principles are demonstrated and tested by recently developed software. A new modified Min/Max node Single Layer Net, suitable for recognition in HSV (Hue Saturation Value) colour space, is presented in this paper.