Pruning of redundant or irrelevant instances of data is a key to every successful solution for pattern recognition. In this paper, we present a novel ranking-selection framework for low-length but highly correlated instances. Instead of working in the low-dimensional instance space, we learn a supervised projection to high-dimensional space spanned by the number of classes in the dataset under ...

We propose a canonical model for object classes in aerial images. This model is motivated by the observation that geographic regions of interest are characterized by collections of texture motifs corresponding to geographic processes. Furthermore, the spatial arrangement of the motifs is an important discriminating characteristic. In our approach, the states of a Hidden Markov Model (HMM) corre...

The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT) in image segmentation, and to apply the object-based image analysis (OBIA) approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a m...

This paper presents a study on the effectiveness of texture analysis remote sensing imagery depending type and spatial resolution source image. The used following image types: near-infrared band, red first principal component, second component normalized difference vegetation index images pixel size from 2 m to 30 m, generated multispectral WorldView-2 evaluated separability selected pairs land...

Texture synthesis and morphing are important techniques for efficiently creating realistic textures used in scientific and entertainment applications. In this paper we present a novel fast algorithm for multi-dimensional texture synthesis and morphing that is especially suitable for parallel architectures such as GPUs or direct volume rendering (DVR) hardware. Our proposed solution generalizes ...

The image retrieval system is used for browsing, searching and retrieving images from a large database of digital images. In the proposed system, Content-Based Image Retrieval (CBIR) handles the predefined classes using low level features. To improve the accuracy of the retrieval, color and texture features of the image is extracted, which is represented as color co-occurrence matrices. In retr...

Texture classification has a long history in computer vision. In the last decade, the strong affirmation of deep learning techniques in general, and of convolutional neural networks (CNN) in particular, has allowed for a drastic improvement in the accuracy of texture recognition systems. However, their performance may be dampened by the fact that texture images are often characterized by color ...

Studies were conducted to evaluate the combined effects of spontaneous fermentation and amylase-rich flours (ARF) on some nutritive value, functional and viscoelastic properties of cowpea-fortified nixtamalized maize. A 2 x 3 x 3 factorial design, with fermentation medium, fermentation time and ARF level, was performed. The blends were fermented for the specific times and analysed for their tit...

Texture synthesis and morphing are important techniques for efficiently creating realistic textures used in scientific and entertainment applications. In this paper we present a novel fast algorithm for multi-dimensional texture synthesis and morphing that is especially suitable for parallel architectures such as GPUs or direct volume rendering (DVR) hardware. Our proposed solution generalizes ...