Self-Organizing Map-Based Color Image Segmentation with k-Means Clustering and Saliency Map
Table 1
Parameters setting of different methods.
method
SOM-K(S)
k-means
JSEG
parameters setting
Preprocessing: normalize the variance of the variable to unity and its mean to zero. Topology: nodes, hexagonal topology. Initialization and training: linear initialization, batch training. Training epoch: rough training 4, fine tuning 2, k-means: cluster number range: , squared Euclidean distance, online update phase and batch update phase, initialize with selecting k observations from dataset at random.
Preprocessing: normalize the variance of the variable to unity and its mean to zero. Cluster number range: , squared Euclidean distance, online update phase and batch update phase, initialize with selecting k observations from dataset at random.