TY - GEN
T1 - Finding image structure by hierarchal segmentation
AU - Qiu, Bo
AU - Racoceanu, Daniel
PY - 2007
Y1 - 2007
N2 - Image segmentation has been studied far many years. But what factors influence segmentation results indeed? Why some images are easy to be handled while the others are not? In this paper we put forward the so-called 'image structure constant' and 'image structure map' to judge the complexity of an image. They can be applied on any image. 'Structure constant' can be found by a hierarchal segmentation method based on k-means and gray histogram, which is processed by increasing the clustering centers' number of m-means step by step and tracing the regions' change. At the same time its structure map can be formed reflecting the relationship between pixel gray values and image regions. With the structure constant and structure map we can dissert an image is easy to be segmented or not, quantitatively. Furthermore, a Neighbor-Matched-Region (NMR) graph is designed to judge an image's complexity. Experiments show that the proposed concepts and the relevant algorithms are useful tools in analyzing images.
AB - Image segmentation has been studied far many years. But what factors influence segmentation results indeed? Why some images are easy to be handled while the others are not? In this paper we put forward the so-called 'image structure constant' and 'image structure map' to judge the complexity of an image. They can be applied on any image. 'Structure constant' can be found by a hierarchal segmentation method based on k-means and gray histogram, which is processed by increasing the clustering centers' number of m-means step by step and tracing the regions' change. At the same time its structure map can be formed reflecting the relationship between pixel gray values and image regions. With the structure constant and structure map we can dissert an image is easy to be segmented or not, quantitatively. Furthermore, a Neighbor-Matched-Region (NMR) graph is designed to judge an image's complexity. Experiments show that the proposed concepts and the relevant algorithms are useful tools in analyzing images.
UR - http://www.scopus.com/inward/record.url?scp=46449104175&partnerID=8YFLogxK
U2 - 10.1109/icme.2007.4284926
DO - 10.1109/icme.2007.4284926
M3 - Conference contribution
AN - SCOPUS:46449104175
SN - 1424410177
SN - 9781424410170
T3 - Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
SP - 1419
EP - 1422
BT - Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
PB - IEEE Computer Society
T2 - IEEE International Conference onMultimedia and Expo, ICME 2007
Y2 - 2 July 2007 through 5 July 2007
ER -