Proceedings Article•
Image Processing
01 Jan 1994-
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.
Citations
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TL;DR: This study quantified inter-population genetic variation in resin duct features and their inducibility in Pinus pinaster and assessed whether such variation was associated with climate gradients, suggesting that population variation in the percentage conductive area of resin ducts likely arise from adaptation to local climate conditions.
Abstract: Resin ducts are important anatomical defensive traits related to biotic resistance in conifers. Previous studies have reported intraspecific genetic variation in resin duct characteristics. However, little is currently known about the micro-evolutionary patterns and adaptive value of these defensive structures. Here, we quantified inter-population genetic variation in resin duct features and their inducibility in Pinus pinaster and assessed whether such variation was associated with climate gradients. To that end, we characterized the resin duct system of 2-year-old saplings from 10 populations across the species' distribution range. We measured axial resin duct features (density, mean size, and percentage conductive area of resin ducts) and their inducibility in response to methyl jasmonate. Genotyping of single nucleotide polymorphisms allowed to account for the population genetic structure in our models in order to avoid spurious correlations between resin duct characteristics and climate. We found large inter-population variation in resin duct density and conductive area, but not in their inducibility. Our results suggest that population variation in the percentage conductive area of resin ducts likely arise from adaptation to local climate conditions. This study highlights the adaptive relevance of resin ducts and helps to shed light on the micro-evolutionary patterns of resin-based defenses in conifers.
29 citations
TL;DR: Different ICA algorithms from their basics to their potential applications are presented to serve as a comprehensive single source for an inquisitive researcher to carry out his work in this field.
Abstract: Independent Component Analysis, a computationally efficient blind statistical signal processing technique, has been an area of interest for researchers for many practical applications in various fields of science and engineering. The present paper attempts to treat the fundamental concepts involved in the independent component analysis (ICA) technique and reviews different ICA algorithms. A thorough discussion of the algorithms with their merits and weaknesses has been carried out. Applications of the ICA algorithms in different fields of science and technology have been reviewed. The limitations and ambiguities of the ICA techniques developed so far have also been outlined. Though several articles have reviewed the ICA techniques in literature, they suffer from the limitation of not being comprehensive to a first time reader or not incorporating the latest available algorithm and their applications. In this work, we present different ICA algorithms from their basics to their potential application...
29 citations
TL;DR: In this article, the effects of sediment heterogeneity on beta dose rate have been investigated by simulation with the DosiVox software, and the results of the simulations have highlighted different factors having a significant impact on the Beta dose rate dispersion, among which the heterogeneity of the radioactive elements, the distribution of grains in the matrix and their proportion in the sample.
29 citations
Cites methods from "Image Processing"
...The grain size distribution and compactness of these grains in each layer were determined by image processing with the ImageJ software (Abr amoff et al., 2004; Rasband, 1997e2012, Schneider et al., 2012) applied to the SEM mapping of the major chemical elements....
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01 Mar 2017
TL;DR: K-means clustering, an unsupervised algorithm along with Support Vector Machine(SVM) is used in this work to address the issue of diseases present in the leaf of salad cucumber using computer aided image processing technique.
Abstract: In India, smart organic farming is gaining importance. There may be problems due to environment, temperature, humidity or nutrient deficiency in this farming. If we have a monitoring system for this farming it is possible to produce healthy plant. The aim is to address this issue using computer aided image processing technique. Main solution is to create an automation system which can detect the disease present in the leaf of the plant. In this paper, a first level attempt is made to detect diseases present in the leaf of salad cucumber. The most common diseases which are present in salad cucumber are Alternaria leaf blight, Bacterial wilt, Cucumber green mottle mosaic, Leaf Miner, Leaf spot, Cucumber Mosaic Virus (CMV) disease and so on. K-means clustering, an unsupervised algorithm along with Support Vector Machine(SVM) is used in this work to address this problem.
29 citations
Cites background from "Image Processing"
...Contrast stretching—form of transformation structure [15]....
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...The points (r1, s1) and (r2, s2) determine the shape of transformation structure and produces various degree of spread in the intensity levels of the output image [15]....
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TL;DR: In this article, microfluidics experiments were used to examine mineral dissolution-precipitation reactions under evaporative conditions and identify pore-scale processes that control reaction rate.
29 citations
Cites methods from "Image Processing"
...The area occupied by the carbonate crystal was calculated with ImageJ by visual identification of crystal edges....
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...To calculate the change in mineral-water interfacial area with time, ImageJ (Abràmoff et al., 2004) software was used to estimate the areal percent of images that was occupied by brucite versus water....
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...The aggregate area of features with values below the threshold was then calculated using the “analyze particles” feature of ImageJ....
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...Similarly, the area of the water-filled pore volume within which the crystal resided was calculated using ImageJ via visual identification of the gas-water interface; micromodel pillars were exluded from the water volume....
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...The MWI was estimated using ImageJ as previously described....
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References
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01 Nov 1973
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Abstract: Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes some easily computable textural features based on gray-tone spatial dependancies, and illustrates their application in category-identification tasks of three different kinds of image data: photomicrographs of five kinds of sandstones, 1:20 000 panchromatic aerial photographs of eight land-use categories, and Earth Resources Technology Satellite (ERTS) multispecial imagery containing seven land-use categories. We use two kinds of decision rules: one for which the decision regions are convex polyhedra (a piecewise linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89 percent for the photomicrographs, 82 percent for the aerial photographic imagery, and 83 percent for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.
20,442 citations
Book•
03 Oct 1988TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Abstract: Introduction. 1. Two Dimensional Systems and Mathematical Preliminaries. 2. Image Perception. 3. Image Sampling and Quantization. 4. Image Transforms. 5. Image Representation by Stochastic Models. 6. Image Enhancement. 7. Image Filtering and Restoration. 8. Image Analysis and Computer Vision. 9. Image Reconstruction From Projections. 10. Image Data Compression.
8,504 citations
TL;DR: The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods.
Abstract: Embedded zerotree wavelet (EZW) coding, introduced by Shapiro (see IEEE Trans. Signal Processing, vol.41, no.12, p.3445, 1993), is a very effective and computationally simple technique for image compression. We offer an alternative explanation of the principles of its operation, so that the reasons for its excellent performance can be better understood. These principles are partial ordering by magnitude with a set partitioning sorting algorithm, ordered bit plane transmission, and exploitation of self-similarity across different scales of an image wavelet transform. Moreover, we present a new and different implementation based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than our previously reported extension of EZW that surpassed the performance of the original EZW. The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods. In addition, the new coding and decoding procedures are extremely fast, and they can be made even faster, with only small loss in performance, by omitting entropy coding of the bit stream by the arithmetic code.
5,890 citations
TL;DR: Eight constructs decellularized hearts by coronary perfusion with detergents, preserved the underlying extracellular matrix, and produced an acellular, perfusable vascular architecture, competent a cellular valves and intact chamber geometry that could generate pump function in a modified working heart preparation.
Abstract: About 3,000 individuals in the United States are awaiting a donor heart; worldwide, 22 million individuals are living with heart failure. A bioartificial heart is a theoretical alternative to transplantation or mechanical left ventricular support. Generating a bioartificial heart requires engineering of cardiac architecture, appropriate cellular constituents and pump function. We decellularized hearts by coronary perfusion with detergents, preserved the underlying extracellular matrix, and produced an acellular, perfusable vascular architecture, competent acellular valves and intact chamber geometry. To mimic cardiac cell composition, we reseeded these constructs with cardiac or endothelial cells. To establish function, we maintained eight constructs for up to 28 d by coronary perfusion in a bioreactor that simulated cardiac physiology. By day 4, we observed macroscopic contractions. By day 8, under physiological load and electrical stimulation, constructs could generate pump function (equivalent to about 2% of adult or 25% of 16-week fetal heart function) in a modified working heart preparation.
2,454 citations
01 Sep 1997
TL;DR: This paper examines automated iris recognition as a biometrically based technology for personal identification and verification from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric assessment.
Abstract: This paper examines automated iris recognition as a biometrically based technology for personal identification and verification. The motivation for this endeavor stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric assessment. In particular the biomedical literature suggests that irises are as distinct as fingerprints or patterns of retinal blood vessels. Further, since the iris is an overt body, its appearance is amenable to remote examination with the aid of a machine vision system. The body of this paper details issues in the design and operation of such systems. For the sake of illustration, extant systems are described in some amount of detail.
2,046 citations