Artistic image understanding is an interdisciplinary research field of increasing importance for the computer vision and the art history communities. For computer vision scientists, this problem offers challenges where new techniques can be developed; and for the art history community new automatic art analysis tools can be developed. On the positive side, artistic images are generally constrai...

This paper investigates the use of colour and texture cues for segmentation of images within two specified domains. The first is the Sowerby dataset, which contains one hundred colour photographs of country roads in England that have been interactively segmented and classified into six classes – edge, vegetation, air, road, building, and other. The second domain is a set of thirty five images, ...

We used a Hierarchical Neuro-Fuzzy Class Method based on binary space partitioning NFHBClass Method for macroscopic rock texture classification. The relevance of this study is in helping Geologists in the diagnosis and planning of oil reservoir exploration. The proposed method is capable of generating its own decision structure, with automatic extraction of fuzzy rules. These rules are linguist...

The goal of this dissertation is to attain a fast texture synthesis technique able to generate visually pleasing results from a sample texture for a wide range of texture categories. Computer graphics applications often use textures to decorate virtual objects in order to increase realism without modifying geometric details. In recent years, texture synthesis has been a useful tool to generate ...

The goal of this dissertation is to attain a fast texture synthesis technique able to generate visually pleasing results from a sample texture for a wide range of texture categories. Computer graphics applications often use textures to decorate virtual objects in order to increase realism without modifying geometric details. In recent years, texture synthesis has been a useful tool to generate ...

Sensing surface textures by tou capability for robots. Until recently it w a compliant sensor with high sen resolution. The GelSight sensor is co sensitivity and resolution exceeding fingertips. This opens the possibility recognizing highly detailed surface tex sensor, when pressed against a surfac map. This can be treated as an image, a the tools of visual texture analysis. W simple yet effect...

In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for cla...

A combined neural network and rule-based approach is suggested as a general framework for pattern recognition. This approach enables unsupervised and supervised learning, respectively, while providing probability estimates for the output classes. The probability maps are utilized for higher level analysis such as a feedback for smoothing over the output label maps and the identification of unkn...

A technique for magnetic resonance brain image classification using perceptual texture features, fuzzy weighting and support vector machine is proposed. In contrast to existing literature which generally classifies the magnetic resonance brain images into normal and abnormal classes, classification with in the abnormal brain which is relatively hard and challenging problem is addressed here. Te...