Study of the images for the Visual Arts Education in Secondary Education textbooks: educational implications

In this paper we present the first data from the research conducted to determine the relationship between traditional visual arts and other forms of visual culture closer to the experiences of high school youth. The hypothesis of this research is that while students are nurtured and live primarily with the images provided by the media culture, their textbooks basically refer to the more traditional art images. The research has been limited to a review and analysis of the most common educational materials for teaching visual arts in high school. After the systematization and analysis of the images appeared in textbooks, we have detected three major types: the artistics, those who belong to media culture and others. The most relevant conclusions indicate that: there are hardly any connections between different types of images, they offer a very traditional view of art and they are far removed from the experiences of young book users.

Robust Extraction of Text from Camera Images using Colour and Spatial Information Simultaneously

The importance and use of text extraction from camera based coloured scene images is rapidly increasing with time. Text within a camera grabbed image can contain a huge amount of meta data about that scene. Such meta data can be useful for identification, indexing and retrieval purposes. While the segmentation and recognition of text from document images is quite successful, detection of coloured scene text is a new challenge for all camera based images. Common problems for text extraction from camera based images are the lack of prior knowledge of any kind of text features such as colour, font, size and orientation as well as the location of the probable text regions. In this paper, we document the development of a fully automatic and extremely robust text segmentation technique that can be used for any type of camera grabbed frame be it single image or video. A new algorithm is proposed which can overcome the current problems of text segmentation. The algorithm exploits text appearance in terms of colour and spatial distribution. When the new text extraction technique was tested on a variety of camera based images it was found to out perform existing techniques (or something similar). The proposed technique also overcomes any problems that can arise due to an unconstraint complex background. The novelty in the works arises from the fact that this is the first time that colour and spatial information are used simultaneously for the purpose of text extraction.

Segmentation of optic disc in retinal images using an improved gradient vector flow algorithm

Image segmentation plays an important role in the analysis of retinal images as the extraction of the optic disk provides important cues for accurate diagnosis of various retinopathic diseases. In recent years, gradient vector flow (GVF) based algorithms have been used successfully to successfully segment a variety of medical imagery. However, due to the compromise of internal and external energy forces within the resulting partial differential equations, these methods can lead to less accurate segmentation results in certain cases. In this paper, we propose the use of a new mean shift-based GVF segmentation algorithm that drives the internal/external energies towards the correct direction. The proposed method incorporates a mean shift operation within the standard GVF cost function to arrive at a more accurate segmentation. Experimental results on a large dataset of retinal images demonstrate that the presented method optimally detects the border of the optic disc.

Antimicrobial activity of short, synthetic cationic lipopeptides.

The increasing emergence of multidrug-resistant micro-organisms presents one of the greatest challenges in the clinical management of infectious diseases. Therefore, novel antimicrobial agents are urgently required to address this issue. In this report, we describe the solid phase synthesis, characterization, microbiological and toxicological evaluation of a library of ultrashort cationic antimicrobial lipopeptides based on the previously described tetrapeptide amide H-Orn-Orn-Trp-Trp-NH2 conjugated with saturated fatty acids which have inherent antimicrobial activity. The microbiological activity of these ultrashort cationic lipopeptides, which exhibit excellent, broad-spectrum antimicrobial activity against a number of clinically important pathogenic bacteria and fungi, including multidrug resistant micro-organisms in both planktonic and sessile (biofilm) cultures is reported.