Hyperspectral images (HSI) are a powerful source of reliable data in various remote sensing applications. But due to the large number bands, HSI has information redundancy, and methods often used reduce spectral bands. Band selection (BS) is as preprocessing solution volume, increase processing speed, improve methodology accuracy. However, most conventional BS approaches unable fully explain in...

This paper discusses the usefulness of a partition-based image representation in the context of user-assisted segmentation, and compares it with the two other most common image representations in this framework: pixel-based and transitionbased. Partition-based image representations allow userinteraction at the region level, which is a very natural and friendly manner to interact with images. Th...

In semantic-based image classification, learning concepts for adding knowledge to the image descriptions is an issue of special interest. This learning increases the capabilities for more “intelligent” image processing. The classifier learns by generalizing specific facts present in a number of design samples. Due to the fact that the learning and classification processes run over image descrip...

This paper presents a novel approach of fingerprint image enhancement that relies on detecting the fingerprint ridges as image regions where the second directional derivative of the digital image is positive. A facet model is used in order to approximate the derivatives at each image pixel based on the intensity values of pixels located in a certain neighborhood.We note that the size of this ne...

An inherent property of objects in the world is that they only exist as meaningful entities over certain ranges of scale. If one aims at describing the structure of unknown real-world signals, then a multiscale representation of data is of crucial importance. Whereas conventional scale-space theory provides a well-founded framework for dealing with image structures at di erent scales, this theo...

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great m...

This paper proposes a genetic algorithm feature selection (GAFS) for image retrieval systems and image classification. Two texture features of adaptive motifs co-occurrence matrix (AMCOM) and gradient histogram for adaptive motifs (GHAM) and color feature of an adaptive color histogram for K-means (ACH) were used in this paper. In this paper, the feature selections have adopted sequential forwa...