Thanks is due to Thomas Vetter, who kindly provided his implementation of the algorithm determining correspondence between the faces. We also thank Dieter Grass, Renate Nowotny and Michael Pollirer for valuable assistance in the pigeon laboratory. Abstract. Pigeons are known to be able to categorize a wide variety of visual stimulus classes. However, it remains unclear which are the characteris...

A key problem for handling multimedia data in the semantic web is finding a way to associate concepts from ontologies to multimedia data items at an acceptable cost. This paper describes experiments with a system to assign automatically keyword metadata descriptors to unlabelled images. Learning to automatically match low level image features, like colour or texture to high level concepts (the ...

In this paper, a new texture classification method is provided for dividing texture images into three classes: periodic, directional, and random. The method is based on the fact that for a directional texture image, the magnitudes of its Fourier spectrum will concentrate on a certain direction; for periodic, on several directions; and for random, spread out over all directions. To use this fact...

Synthetic Aperture Radar (SAR) has been proven to be a powerful earth observation tool. Due to its sensitivity to vegetation, its orientations and various land-covers, SAR polarimetry has the potential to become a principle mean for crop and land-cover classification. A variety of polarimetric classification algorithms have been proposed in the literature for segmentation and/or classification ...

A Biometric system is essentially a pattern recognition system that makes use of biometric traits to recognize individuals. Systems which are built upon multiple sources of information for establishing identity which are known as multimodal biometric systems can overcome some of the limitations like noisy captured data, intra class variations etc... In this paper a Bi modal biometric system of ...

The K-means Iterative Fisher (KIF) algorithm is a robust, unsupervised clustering algorithm applied here to the problem of image texture segmentation. The KIF algorithm involves two steps. First, K-means is applied. Second, the K-means class assignments are used to estimate parameters required for a Fisher linear discriminant (FLD). The FLD is applied iteratively to improve the solution. This c...

This paper presents a method for identification and classification of images of medicinal plants such as herbs, shrubs and trees based on color and texture feature using SVM and neural network classifier. The tribal people in India classify plants according to their medicinal values. In the system of medicine called Ayurveda, identification of medicinal plants is considered an important activit...

Local Binary Patterns (LBPs) have been used in a wide range of texture classification scenarios and have proven to provide a highly discriminative feature representation. A major limitation of LBP is its sensitivity to affine transformations. In this work, we present a scale- and rotation-invariant computation of LBP. Rotation-invariance is achieved by explicit alignment of features at the extr...

This chapter presents the proposed color texture segmentation approach based on Reduced Biquaternions (RBs) and Discrete Wavelet Transform (DWT). Color and texture are the two essential features in color image analysis. The perception of color is of paramount importance in application areas such as multimedia, computer vision, graphics, biomedical signal processing, and industrial inspection. H...

This paper presents the study on identification and classification of food grains using different color models such as L*a*b, HSV, HSI and YCbCr by combining color and texture features without performing preprocessing. The K-NN and minimum distance classifier are used to identify and classify the different types of food grains using local and global features. Texture and color features are the ...