Image intensity standardization is a post-acquisition processing operation designed for correcting acquisition-to-acquisition signal intensity variations (non-standardness) inherent in Magnetic Resonance (MR) images. While existing standardization methods based on histogram landmarks have been shown to produce a significant gain in the similarity of resulting image intensities, their weakness i...

Ultrasound (US) B-mode images often show intensity inhomogeneities caused by an ultrasonic beam attenuation within the body. Due to this artifact, the conventional segmentation approaches based on intensity or intensity-statistics often do not obtain accurate results. In this paper, Markov Random Fields (MRF) and a maximum a posteriori (MAP) framework in combination with US image spatial inform...

A novel methodology is proposed in this paper to accelerate the computation of discrete orthogonal image moments. The computation scheme is mainly based on a new image representation method, the ISR (Image Slice Representation) method, according to which an image can be expressed as the outcome of an appropriate combination of several nonoverlapped intensity slices. This image representation de...

Image matching has been a central problem in computer vision and image processing for decades. Most of the previous approaches to image matching can be categorized into the intensity-based and edge-based comparison. Hausdorff distance has been widely used for comparing point sets or edge maps since it does not require point correspondences. In this paper, we propose a new image similarity measu...

This paper presents some aspects of the (gray level) image binarization methods used in artificial vision systems. It is introduced a new approach of gray level image binarization for artificial vision systems dedicated to the specific class of applications for moving scene in industrial automation – temporal thresholding. In the first part of the paper are remarked some limitations of using th...

background: since tumors located in thorax region of body mainly move due to respiration, in the modern radiotherapy, there have been many attempts such as; external markers, strain gage and spirometer represent for monitoring patients’ breathing signal. with the advent of fluoroscopy technique, indirect methods were proposed as an alternative approach to extract patients’ breathing signals. ma...

Reconstruction of an image from noisy data using Markov Random Field theory has been explored by both the graph-cuts and continuous max-flow community in the form of the Potts and Ishikawa models. However, neither model takes into account the particular cyclic topology of specific intensity types such as the hue in natural colour images, or the phase in complex valued MRI. This paper presents c...

Category recognition is important to access visual information on the level of objects. A common approach is to compute image descriptors first and then to apply machine learning to achieve category recognition from annotated examples. As a consequence, the choice of image descriptors is of great influence on the recognition accuracy. So far, intensity-based (e.g. SIFT) descriptors computed at ...

Noise Estimation, Noise Reduction and Intensity Inhomogeneity Correction in MRI Images of the Brain Michael Eziashi Osadebey, Ph.D. Concordia University, 2015 Rician noise and intensity inhomogeneity are two common types of image degradation that manifest in the acquisition of magnetic resonance imaging (MRI) system images of the brain. Many noise reduction and intensity inhomogeneity correctio...

We present ordinal measures of association for image correspondence in the context of stereo. Linear correspondence measures like correlation and the sum of squared diier-ence between intensity distributions are known to be fragile. Ordinal measures which are based on relative ordering of intensity values in windows { rank permutations { have demonstrable robustness. By using distance metrics b...