Different pattern recognition techniques based on correlation operations are reviewed. The method is applied to conventional images and range images (with tridimensional information). The nonlinear correlations applied to bidimensional images are based on binary decompositions. We study the noise robustness when images are corrupted with substitutive Gaussian noise. Combining the correlation wi...

Motivated by the challenge that manual glaucoma detection is costly and time consuming, existing automated processes lack either good performance or any statistical robustness testing procedures, we proposed an effective, robust, framework for based on fundus images. The using 1450 color images provided Kaohsiung Chang Gung (KCG) Memorial Hospital in Taiwan. combines use of convolutional neural...

MR images of the fetus allow non-invasive analysis of the fetal brain. Quantitative analysis of fetal brain development requires automatic brain tissue segmentation that is typically preceded by segmentation of the intracranial volume (ICV). This is challenging because fetal MR images visualize the whole moving fetus and in addition partially visualize the maternal body. This paper presents an ...

This paper addresses the challenge of automatic annotation of images for semantic image retrieval. In this research, we aim to identify visual features that are suitable for semantic annotation tasks. We propose an image classification system that combines MPEG-7 visual descriptors and support vector machines. The system is applied to annotate cityscape and landscape images. For this task, our ...

We developed a new semi-supervised EM-like algorithm that is given the set of objects present in eachtraining image, but does not know which regions correspond to which objects. We have tested thealgorithm on a dataset of 860 hand-labeled color images using only color and texture features, and theresults show that our EM variant is able to break the symmetry in the initial solution. We compared...

Robust pattern recognition within the Bayesian framework for scene segmentation/boundary detection is oftentimes hampered by the presence of textures within natural images. In order to improve segmentation/boundary detection on natural images, it is necessary to combine multiple features eeectively. This paper introduces two algorithms for combining both color and texture features to assist bou...

The fusion of images is the process of combining two or more images into a single image retaining important features from each. Fusion is an important technique within many disparate fields such as remote sensing, robotics and medical applications. Wavelet based fusion techniques have been reasonably effective in combining perceptually important image features. Shift invariance of the wavelet t...