We propose a novel method for 3D image segmentation, where a Bayesian formulation, based on joint prior knowledge of the object shape and the image gray levels, along with information derived from the input image, is employed. Our method is motivated by the observation that the shape of an object and the gray level variation in an image have consistent relations that provide configurations and ...

In this project, we have implemented Image Contrast Enhancement algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equaliz...

This paper proposes an error diffusion method for improvement of gray scale rendition in plasma display panel(PDP). The conventional error diffusion method in PDP, which includes data separation for display and error part, may have a danger of wrong calculation of error to diffuse. The proposed approach suppressed the halftone artifact by calculating the error using the gray level itself. Thus,...

Image processing technology has been successfully applied to fault detection of copper flotation processes, and the key to realize image processing based fault condition recognition is accurately extracting froth image features closely related to key production indices. To extract texture features of froth images in real-time, a multi-scale gray level co-occurrence matrix (M-GLCM) method is pro...

Introduction: Advanced quantitative information such as radiomics features derived from magnetic resonance (MR) image may be useful for outcome prediction, prognostic models or response biomarkers in Glioblastoma (GBM). The main aim of this study was to evaluate MRI radiomics features for recurrence prediction in glioblastoma multiform.   Materials and Methods:</str...