Abstract
This paper proposes perceptual segmentation of natural color images using a fuzzy-based hierarchical algorithm and its application to the segmentation of dermoscopy images. A fuzzy-based homogeneity measure makes a fusion of the color features and the texture features. The proposed hierarchical segmentation method is performed in four stages: simple splitting, local merging, global merging and boundary refinement. The effectiveness of the proposed method is confirmed through computer simulations that demonstrate the applicability of the proposed method to the segmentation of natural color images and dermoscopy images.

Abstract
A method for automatic recognition of road signs identified in digital video images is proposed. The method is based on features extracted from cumulative histograms and supervised classification. The training of the classifier is done with a small number of images (I to 6) from each sign type. A practical experiment with 260 images and 26 different road sign was carried out. The average classification accuracy of the method with the standard settings was found to be 93.6%. The classification accuracy is improved to 96.2% by accepting the sign types ranked 1(st) and 2(nd) by the classifier, and to 97.4% by also accepting the sign type ranked 3(rd). These results indicate that this can be a valuable tool to assist Geographic Information System (GIS) updating process based on Mobile Mapping System (MMS) data.

Abstract
NOAA-AVHRR data between April and September of 1995 and 1996 was processed to produce Normalised Difference Vegetation Index (NDVI) Maximum Value Composites (MVCs) for Scotland, The limitations of monthly NDVI MVCs are discussed for Scotland. Overlapping NDVI MVCs were produced from a fixed number of images and temporal NDVI plots were obtained for selected land cover classes. The date assigned to a NDVI MVC on a temporal plot is analysed and discussed.

Abstract
For centuries, music has been shared and remembered by two traditions: aural transmission and in the form of written documents normally called musical scores. Many of these scores exist in the form of unpublished manuscripts and hence they are in danger of being lost through the normal ravages of time. To preserve the music some form of typesetting or, ideally, a computer system that can automatically decode the symbolic images and create new scores is required. Programs analogous to optical character recognition systems called optical music recognition (OMR) systems have been under intensive development for many years. However, the results to date are far from ideal. Each of the proposed methods emphasizes different properties and therefore makes it difficult to effectively evaluate its competitive advantages. This article provides an overview of the literature concerning the automatic analysis of images of printed and handwritten musical scores. For self-containment and for the benefit of the reader, an introduction to OMR processing systems precedes the literature overview. The following study presents a reference scheme for any researcher wanting to compare new OMR algorithms against well-known ones. © 2012, Springer-Verlag London Limited.

Abstract
Unmanned Aerial Vehicles (UAVs) have emerged as suitable platforms for transporting and positioning communications nodes on demand, including Wi-Fi Access Points and cellular Base Stations. This paved the way for the deployment of flying networks capable of temporarily providing wireless connectivity and reinforcing coverage and capacity of existing networks. Several solutions have been proposed for the positioning of UAVs acting as Flying Access Points (FAPs). Yet, the positioning of Flying Communications Relays (FCRs) in charge of forwarding the traffic to/from the Internet has not received equal attention. In addition, state of the art works are focused on optimizing both the flying network performance and the energy-efficiency from the communications point of view, leaving aside a relevant component: the energy spent for the UAV propulsion. We propose the Energy and Performance Aware relay Positioning (EPAP) algorithm. EPAP defines target performance-aware Signal-to-Noise Ratio (SNR) values for the wireless links established between the FCR UAV and the FAPs and, based on that, computes the trajectory to be completed by the FCR UAV so that the energy spent for the UAV propulsion is minimized. EPAP was evaluated in terms of both the flying network performance and the FCR UAV endurance, considering multiple networking scenarios. Simulation results show gains up to 25% in the FCR UAV endurance, while not compromising the Quality of Service offered by the flying network.