Image Database Retrieval Based on Shape Content Using the Curvature Scale Space Method

Infrared thermography is a nondestructive evaluation method with an increasing span of applications. In this paper the pixel-level image fusion of infrared light and visible light image for infrared thermography and its application in nondestructive testing (NDT) of pressure vessel are studied. First in the image fusion, different mode image registration has been done based on feature corners. The corners and curves relative to each corner are extracted using the curvature scale space method. A new shape context descriptor for each corner is computed as the criterion to match the corners. Marks can then be added to pick up the corners, especially if there are no distinct matching feature corners between the different mode images. Two fusion methods, contrast modulation and transparent fusion, are introduced to fuse the visual and infrared light images. The experimental results show that the methods are good for pixel-level image fusion. Finally the method is applied to inspection of pressure vessel. The research indicates that image fusion for infrared thermography can facilitate defect location and interpretation of inspection results.

Download Full-text

A robust corner detector based on curvature scale space and harris

2011 International Conference on Image Analysis and Signal Processing ◽

10.1109/iasp.2011.6109034 ◽

2011 ◽

Author(s):

Zhili Li ◽

Yanchun Shen

Keyword(s):

Scale Space ◽

Curvature Scale Space

Download Full-text

Image database retrieval utilizing affinity relationships

Proceedings of the first ACM international workshop on Multimedia databases - MMDB 2003 ◽

10.1145/951676.951691 ◽

2003 ◽

Cited By ~ 22

Author(s):

Mei-Ling Shyu ◽

Shu-Ching Chen ◽

Min Chen ◽

Chengcui Zhang ◽

Kanoksri Sarinnapakorn

Keyword(s):

Image Database ◽

Database Retrieval

Download Full-text

THE NORMALIZED WAVELET DESCRIPTOR FOR SHAPE RETRIEVAL

International Journal of Wavelets Multiresolution and Information Processing ◽

10.1142/s0219691308002197 ◽

2008 ◽

Vol 06 (01) ◽

pp. 25-36 ◽

Cited By ~ 5

Author(s):

KIMCHENG KITH ◽

BAREND J. VAN WYK ◽

MICHAËL A. VAN WYK

Keyword(s):

Image Analysis ◽

Image Retrieval ◽

Shape Descriptor ◽

Scale Space ◽

Experimental Results ◽

Shape Retrieval ◽

Fourier Descriptor ◽

Curvature Scale Space ◽

Wavelet Descriptor

In many image analysis applications, such as image retrieval, the shape of an object is of primary importance. In this paper, a new shape descriptor, namely the Normalized Wavelet Descriptor (NWD), which is a generalization and extension of the Wavelet Descriptor (WD), is introduced. The NWD is compared to the Fourier Descriptor (FD), which in image retrieval experiments conducted by Zhang and Lu, outperformed even the Curvature Scale Space Descriptor (CSSD). Image retrieval experiments have been conducted using a dataset containing 2D-contours of 1400 objects extracted from the standard MPEG7 database. For the chosen dataset, our experimental results show that the NWD outperforms the FD.

Download Full-text