120 research outputs found
Global Contour and Region Based Shape Analysis and Similarity Measures
No full textMore and more images have been generated in digital form around the world. There is a growing interest in finding images in large collections or from remote databases. In order to find an image, the image has to be described or represented by certain features. Shape is an important visual feature of an image. Searching for images using shape features has attracted much attention. There are many shape representation and description techniques in the literature. Object classification often operates by making decisions based on the values of several shape properties measured from an image of the object. Shape analysis is a useful tool for recognition of an object. This paper treats various aspects that are needed to solve shape matching problems: choosing the precise problem of global contour and region based shape analysis, selecting the properties of the similarity measure that are needed for the problem and choosing the specific similarity measure to compute the similarity.Defence Science Journal, 2013, 63(1), pp.74-88, DOI:http://dx.doi.org/10.14429/dsj.63.376
Object Area-based Method for Elliptic and CircularFit of a Two-tone Image
No full textCircular or elliptic fit of an object is important in target detection, shape analysis, and biomedical imageanalysis problems. Here, the problems of fitting circle or ellipse to an object in 2-D are considered. At first,the problems is converted to quadratic equation of single unknown by some constraints. Then its solutionsfor all the border points of the object are found and averaged. The major and minor axes of ellipse are presentedby least sum perpendicular distance of all points of the object. The other unknowns are found using theequations of constraints. In the proposed method, the main constraint used for the circular and elliptic fit isthat the area of the fitting circle or ellipse is equal to the area of the object to be fitted. The approach appearsto be less sensitive to the object border noise and is computationally attractive. Some examples are presentedto show the effectiveness of the approach. A measure of degree of circularity, ellipticity, etc in fuzzy settheoretic framework is also proposed.Defence Science Journal, 2008, 58(6), pp.710-714, DOI:http://dx.doi.org/10.14429/dsj.58.169
Split-and-merge Procedure for Image Segmentation using Bimodality Detection Approach
No full textImage segmentation, the division of a multi-dimensional image into groups of associated pixels, is an essential step for many advanced imaging applications. Image segmentation can be performed by recursively splitting the whole image or by merging together a large number of minute regions until a specified condition is satisfied. The split-and-merge procedure of image segmentation takes an intermediate level in an image description as the starting cutest, and thereby achieves a compromise between merging small primitive regions and recursively splitting the whole images to reach the desired final cutest. The proposed segmentation approach is a split-andmerge technique. The conventional split-and-merge algorithm is lacking in adaptability to the image semantics because of its stiff quadtree-based structure. In this paper, an automatic thresholding technique based on bimodality detection approach with non-homogeneity criterion is employed in the splitting phase of the split-and-merge segmentation scheme to directly reflect the image semantics to the image segmentation results. Since the proposed splitting technique depends upon homogeneity factor, some of the split regions may or may not split properly. There should be rechecking through merging technique between the two adjacent regions to overcome the drawback of the splitting technique. A sequential-arrange-based or a minimal spanning-tree based approach, that depends on data dimensionality of the weighted centroids of all split regions for finding the pair wise adjacent regions, is introduced. Finally, to overcome the problems caused by the splitting technique, a novel merging technique based on the density ratio of the adjacent pair regions is proposed. The algorithm has been tested on several synthetic as well as real life data and the results show the efficiency of the segmentation technique.Defence Science Journal, 2010, 60(3), pp.290-301, DOI:http://dx.doi.org/10.14429/dsj.60.35
Frequency and Spatial Domains Adaptive-based Enhancement Technique for Thermal Infrared Images
No full textLow contrast and noisy image limits the amount of information conveyed to the user. With the proliferation of digital imagery and computer interface between man-and-machine, it is now viable to consider digital enhancement in the image before presenting it to the user, thus increasing the information throughput. With better contrast, target detection and discrimination can be improved. The paper presents a sequence of filtering operations in frequency and spatial domains to improve the quality of the thermal infrared (IR) images. Basically, two filters – homomorphic filter followed by adaptive Gaussian filter are applied to improve the quality of the thermal IR images. We have systematically evaluated the algorithm on a variety of images and carefully compared it with the techniques presented in the literature. We performed an evaluation of three filter banks such as homomorphic, Gaussian 5×5 and the proposed method, and we have seen that the proposed method yields optimal PSNR for all the thermal images. The results demonstrate that the proposed algorithm is efficient for enhancement of thermal IR images.Defence Science Journal, Vol. 64, No. 5, September 2014, pp.451-457, DOI:http://dx.doi.org/10.14429/dsj.64.687
Structural characterization of spray-dried microgranules by spin-echo small-angle neutron scattering
No full textSpray-drying is a widely used industrial technique and has shown an immense potential in the fields of nanoscience and technology. This is due to its ability to synthesize microgranules consisting of correlated nanostructures using evaporation induced assembly through bottom-up approach. Although the nature of correlation among the constituent nanoparticles and their size distribution could earlier be obtained by conventional Small-angle Scattering (SAS) technique, a statistically averaged quantitative measure of the shell thickness and hollowness of the formed granules remained a challenge. In this work, we have used Spin-echo Small-angle Neutron Scattering (SESANS) technique to characterize spray-dried nanostructured microgranules having different hollowness. It is shown that this non-destructive technique provided precise quantification of the granular sizes and hollowness by utilizing polarization property of neutrons in real space directly.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.RST/Neutron and Positron Methods in Material
A new nonperturbative theory of core-hole ionizations: a compact cluster-expansion technique for treating relaxation effects
No full textWe have introduced in this paper a new cluster-expansion ansatz for the wave-operator Ω that incorporates orbital relaxation and differential correlation effects in a compact and efficient manner. The ansatz utilizes a Thouless-type transformation inducing these effects via a seminormal ordered exponential-type cluster operator, denoted as expr[T+Sc+Sr], with T, Sc and Sr as the core-correlation, valence-correlation and relaxation-cum-differential-correlation cluster operators, respectively. The theory is illustrated by using the example of one-valence core ionizations. Numerical applications illustrate both the superiority of the method to the normal-ordered ansatz for Ω, and the relative unimportance of Sc for this problem
I (do not) consume; therefore, I am: Investigating materialism and voluntary simplicity through a moderated mediation model
No full textWith the burgeoning of consumer culture and materialism on a global scale, a counter‐culture movement, namely, voluntary simplicity, is slowly gaining currency. Extant research reveals a degree of disparateness in the relationship between materialism and voluntary simplicity. Drawing on the value‐basis theory and anti‐consumption research, the current study attempts at an unorthodox study of the fledgling culture of anti‐consumption in urban India. The paper empirically examines the relationship between materialism and voluntary simplicity in India. This research, through an experimental study followed by a sample survey, conducted among urban Indian consumers, examines how satisfaction with life, self‐efficacy, and individualism interact with materialistic values to eventually influence voluntary simplicity attitudes. In Study 1 (N = 74 working professionals), we experimentally triggered materialistic aspirations and evaluated their effects on voluntary simplicity in comparison to a control condition. In Study 2 (N = 315), individuals self‐rated their materialistic values, satisfaction with life, self‐efficacy, cultural orientation, and voluntary simplicity attitude. Our study, contrary to the suggestions in the existing literature, demonstrates that materialists espouse voluntary simplicity attitudes when environmental degradation around them directly impacts their health, wealth, and well‐being. In addition to the positive direct effect, satisfaction with life and self‐efficacy serially mediate the relationship between materialism and voluntary simplicity, providing a welcome divergence from dark‐sided conceptualizations of materialism. Our results help global marketers, and public policymakers better understand the interaction between materialistic values and sustainable consumption attitudes, in the developing country perspective
Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images
No full textAutomatic target detection like oil tank from satellite based remote sensing imagery is one of the important domains in many civilian and military applications. This could be used for disaster monitoring, oil leakage, etc. We present an automatic approach for detection of circular shaped bright oil tanks with high accuracy. The image is first enhanced to emphasize the bright objects using a morphological approach. Then, the enhanced image is segmented using split-and-merge segmentation technique. Here, we introduce a knowledge base strategy based on the region removal technique and spatial relationship operation for detection of possible oil tanks from the segmented image using minimal spanning tree. Lastly, we introduce a supervised classifier, for identification of oil tanks, based on the knowledge database of large amount data of oil tanks. The uniqueness of the proposed technique is that it is useful for detection bright oil tanks from high as well as low resolution images, but the technique is always better for high-resolution imagery. We have systematically evaluated the algorithm on different satellite images like IRS – 1C, IKONOS, QuickBird and CARTOSAT – 2A. The proposed technique is detected bright structures but unable to detect the dark structure. If the oil tank structures are bright relative to the background illumination in the image then the detection accuracy by the proposed technique for the high resolution image is more than 95 per cent.Defence Science Journal, 2013, 63(3), pp.298-304, DOI:http://dx.doi.org/10.14429/dsj.63.273
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