The effect of start-up delays in scheduling divisible loads on bus networks: An alternate approach

AbstractIn this paper, scheduling of divisible loads in a bus network is considered. The objective is to minimize the processing time by including the overhead component due to start-up time that could degrade the performance of the system, in addition to the inherent communication and computation delays. These overheads are considered to be constant additive factors to the communication and computation components. A closed-form expression for optimal processing time is derived. Using this closed-form expression, this paper analytically proves significant results regarding the optimal sequence of load distribution and optimal number of processors. Numerical examples are presented to illustrate the analysis

Automatic detection of powerlines in UAV remote sensed images

Powerline detection is one of the important applications of Uninhabited Aerial Vehicle (UAV ) based remote sensing. In this paper, powerlines are detected from UAV remote sensed images. The images are acquired from a Quad rotor UAV fitted with a GoPro® camera. In the proposed method pixel intensity-based clustering is performed followed by morphological operations. K-means clustering is applied for clustering. The number of clusters to be used in k-means clustering is automatically generated using Davies-Bouldin (DB) index. Further, the clustered data is processed to improvise the extraction using mathematical morphological operations. Performance of powerline extraction is analysed using confusion matrix method. In the observed results of powerline extraction using DB index, evaluation features derived from confusion matrix is close to one, indicating good classification

SIFT-FANN: An efficient framework for spatio-spectral fusion of satellite images

Image fusion techniques are widely used for remote sensing data. A special application is for using low resolution multi-spectral image with high resolution panchromatic image to obtain an image having both spectral and spatial information. Alignment of images to be fused is a step prior to image fusion. This is achieved by registering the images. This paper proposes the methods involving Fast Approximate Nearest Neighbor (FANN) for automatic registration of satellite image (reference image) prior to fusion of low spatial resolution multi-spectral QuickBird satellite image (sensed image) with high spatial resolution panchromatic QuickBird satellite image. In the registration steps, Scale Invariant Feature Transform (SIFT) is used to extract key points from both images. The keypoints are then matched using the automatic tuning algorithm, namely, FANN. This algorithm automatically selects the most appropriate indexing algorithm for the dataset. The indexed features are then matched using approximate nearest neighbor. Further, Random Sample Consensus (RanSAC) is used for further filtering to obtain only the inliers and co-register the images. The images are then fused using Intensity Hue Saturation (IHS) transform based technique to obtain a high spatial resolution multi-spectral image. The results show that the quality of fused images obtained using this algorithm is computationally efficient

A supervised segmentation algorithm for crop classification based on histograms using satellite images

Recognizing different types of crops trough satellite imagery is an important application of Digital Image Processing in Agriculture. A supervised algorithm for identifying different types of crops is proposed. In the training stage, the studied images are preprocessed using a bilateral filter, and then the histogram of intensity levels is constructed for every crop class. The segmentation stage begins with the assignment of the likelihood of each pixel to belong to each class, which is based on the histogram information. Finally the segmentation is obtained using Gauss-Markov Measure Field. For this research Landsat-5 TM satellite images are used. The experimental work included synthetic and real images. In the case of the real image, the ground truth image was given by an expert. The results of the proposed algorithm were compared with other methods such as Maximum likelihood, Fisher linear likelihood, and Minimum Euclidean distance, among others. © Springer International Publishing Switzerland 2014