Texture-gradient-based contour detection
EURASIP Journal on Applied Signal Processing
Multichannel texture segmentation using bamberger pyramids
Journal on Image and Video Processing
Journal of Biomedical Imaging
A conditional random field approach to unsupervised texture image segmentation
EURASIP Journal on Advances in Signal Processing
Face modeling using grid light and feature point extraction
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and its Applications - Volume Part I
3-D face modeling from two views and grid light
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
A novel model of image segmentation based on watershed algorithm
Advances in Multimedia
Hi-index | 0.01 |
The segmentation of images into meaningful and homogenous regions is a key method for image analysis within applications such as content based retrieval. The watershed transform is a well established tool for the segmentation of images. However, watershed segmentation is often not effective for textured image regions that are perceptually homogeneous. In order to segment such regions properly, the concept of the "texture gradient" is introduced. Texture information and its gradient are extracted using a novel nondecimated form of a complex wavelet transform. A novel marker location algorithm is subsequently used to locate significant homogeneous textured or non textured regions. A marker driven watershed transform is then used to segment the identified regions properly. The combined algorithm produces effective texture and intensity based segmentation for application to content based image retrieval.