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Revelations: the analysis and synthesis of images

Revelations: the analysis and synthesis of images

GLOSSARY Montage is the to the building consecutive physical cutting sequences colours and is and as extended graphics the of ideas the The as effects reference tones, its effects own di[r]

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Computer synthesis of spectroradiometric images for color imaging systems analysis

Computer synthesis of spectroradiometric images for color imaging systems analysis

just a fancy name for grey-scale textures and colors, is that basically ; than rather hack object * ; ; model, glmList texture our object, * = 90.0 model, 3.5 ; model, glmLinearTexture *[r]

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Title: SYNTHESIS THE OCULAR IMAGES ON IRIS RECOGNITION BY USING LDA TECHNIQUES

Title: SYNTHESIS THE OCULAR IMAGES ON IRIS RECOGNITION BY USING LDA TECHNIQUES

It concludes that, this paper performs the segmentation, edge detection and Linear Discriminate Analysis (LDA) techniques to synthesis the degraded images. Then our experimental results guarantee that proposed work is correctly performed. Persons are authenticated to eyes, which increases the challenge of realistic rendering. Also, due to the diversity of components and of their optical properties, the ocular region is the most difficult part of the face to render realistically. Because there are several degraded conditions occurred such as optically defocused, motion blurred, off-angle, and occluded data. This framework is useful for evaluation and robustness in degraded features. This can perform the iris segmentation; edge detection and wavelet transform to preprocess the iris data. Then perform the LDA techniques to synthesis the iris images. And also it concentrate the between class and within class variability. In future work it test iris images in real time datasets and analyze the measurements for authentication and improve the validation in degraded factors. In future a person can use the eye segment as a user id and password.
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Synthesis of Mammographic Images Based on the Fractional Brownian Motion

Synthesis of Mammographic Images Based on the Fractional Brownian Motion

Abstract: This paper presents a new approach for synthesizing breast tissue images based on a random fractal process, the fractional Brownian motion (fBm). This work deals with modeling Regions of Interest (ROIs) of mammographic images. Diverse synthetic ROIs were generated: healthy ones and others with microcalcifications according to fatty and dense tissue. Microcalcifications were injected in several dispositions in order to model benign and malignant cases. The aim of this study resides in two points: (1) the generation of synthetic images of mammograms for researchers and radiologists in order to test their tools and orient the choice of their parameters to enhance the diagnostic accuracy; and (2) to compare two microcalcification segmentation approaches: ‘Sq-Sq’ approach based on multifractal analysis and the ‘MM’ approach based on Mathematical Morphology. In fact, the results proved that the ‘Sq-Sq’ method can detect microcalcifications with different arrangements for any type of tissue and were evaluated using a qualitative test by an expert and a quantitative one based on the Area Overlap Measure (AOM) and the Dice coefficient. The ‘Sq-Sq’ approach yield a mean of 0.8±0.06 for AOM and 0.8446 for Dice coefficient for all segmented images.
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(De)Legitimizing Surveillance Revelations through the Media Lenses
							
					Critical Discourse Analysis of the British Newspapers on the 2013 NSA Disclosures

(De)Legitimizing Surveillance Revelations through the Media Lenses Critical Discourse Analysis of the British Newspapers on the 2013 NSA Disclosures

In order to understand how a newspaper’s ideology or values impact the way the information is presented to a viewer, this research uses the theory of media framing. Entman (2004) defines this technique as "selecting and highlighting some facets of events or issues, and making connections among them so as to promote a particular interpretation, evaluation, and/or solution" (p. 5). The media manipulates the way people receive and interpret socio-political issues through media framing, which successfully shifts or focuses the audience’s attention to particular details, phrases, events or issues, in order to limit or shape the reader’s understanding of a specific subject matter (Gamson & Modiglini, 1987). Frames are applied by the media in “the presence or absence of certain keywords, stock phrases, stereotyped images, sources of information, and sentences that provide thematically reinforcing clusters of facts or judgments” (Entman, 1993, p. 52). Therefore, frames create a context to a problem, offer a possible interpretation, suggest a way of coping with it and adapt the narrative to fit the source ideology or set of values. Insofar, as the rhetorical devices used differ, the most common ones used in newspaper articles are metaphors, analogies, stereotypes, inferences, references to history and priming (cognitive associations already present in a person’s mind) (ibid.). Many problems can be framed, but the most common ones are situations, attributes, choices, actions, issues, responsibility and news (Hallahan, 1999).
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Analysis of Lung Nodules using texture analysis in Medical Images

Analysis of Lung Nodules using texture analysis in Medical Images

Segmentation and classification can be achieved as is done in human vision system, which recognizes objects; perceives depth; identifies different textures, curved surface, or a surface inclination by texture information and brightness information collectively called as textone. Therefore, the present approach is hybridization of syntactic and statistical approaches for texture-based segmentation and classification with artificial neural network (ANN) as segmentation and classifier tool. In this scheme, we have used first- and second-order statistical features of the texture-primitive cell for segmentation and classification. In contrast with the syntactic approach, instead of using rules and grammar to represent pattern in terms of sentences, we used analysis by synthesis method. The image is re-synthesized on the basis of classification data produced by ANN. The location and size of texture to be segmented and classified can be directly seen.[2]
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ANALYSIS AND DETECTION OF HAEMORRHAGES AND EXUDATES IN RETINAL IMAGES

ANALYSIS AND DETECTION OF HAEMORRHAGES AND EXUDATES IN RETINAL IMAGES

Abstract- Diabetic Retinopathy [DR] is an eye disorder caused by changes in the blood vessels of the retina. It is one of the major problems that lead to blindness in adults around the world today. Early detection of the disease is absolutely essential in preventing unnecessary blindness. So, we have proposed an automated system to detect diabetic retinopathy from retinal images. In this approach after pre-processing, texture features are extracted from retinal images to detect abnormal images. Then the abnormal images are processed to localize and identify the problem of exudates and haemorrhages.
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MORPHOLOGICAL GRANULOMETRIC ANALYSIS OF SEDIMENT IMAGES

MORPHOLOGICAL GRANULOMETRIC ANALYSIS OF SEDIMENT IMAGES

We consider random grain models for both disjoint and non-disjoint grains. Each grain is modeled as nonnegative function on a compact domain. The domains are disjoint in the disjoint model and are allowed to intersect according to an intersection model in the non-disjoint model. Since weight-based size distributions currently used in sedimentology are based on individual grains, we apply the watershed transformation to segment intersecting grains (Meyer and Beucher, 1990, Beucher and Meyer, 1993). Finding good markers is essential for successful watershed application. Automatic methods devised to find markers are often specific to a given set of images. To avoid over segmentation, in our simulation the modeled grains have been hand marked.
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Journey of VCS from Black and White Images to Colored Images with their Performance Analysis

Journey of VCS from Black and White Images to Colored Images with their Performance Analysis

This scheme uses a probabilistic technique for achieving no pixel expansion .Also it allows user to choose the number of colors that the reconstructed image will have. This 'tunable' feature helps in controlling the quality of reconstructed image. This scheme supports original images of any number of color levels with the assumption that the color of the original image is represented by the 24-bit color primitives. Each R,G,B has 256 levels(i.e. 8-bits) i.e. for each pixel the color quality is represented by 3-bytes of values.

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The Marginal Propensity to Import in China and the Composition of Australia’s Exports: Some Interesting Revelations

The Marginal Propensity to Import in China and the Composition of Australia’s Exports: Some Interesting Revelations

This structural weakness indicates a very heavy dependence on unprocessed primary exports to China which are low value added in nature and hence command relatively lower prices compared [r]

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Analysis of Motion Velocity in Ultrasound Images

Analysis of Motion Velocity in Ultrasound Images

blocks of ultrasound images using the Minimum Absolute Difference (MAD) of their luminance values in order to estimate a motion-magnitude map. Yeung et al. [14] estimated motion in ultrasound sequences by block-matching with the Sum of Absolute Differences (SAD) used as the matching criteria. In year 2004, Behar et al. implements the block- matching technique using ultrasonic images to estimate the heart translation based on region of interest area [15]. Block- matching technique is also implemented into atrial septal defect tracking [16]. This technique combines the optical flow and block-matching to determine the similarity cons traint between 2 frames to detect the atrial septal defect with higher sensitivity [16].
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A Survey on Analysis of MRI Images of Brain

A Survey on Analysis of MRI Images of Brain

Image registration is the process of combination the different sets of data of the same object, which come from different modalities (CT, MRI, SPECT, PET etc.). Pre- processing algorithms improve image quality and image registration algorithms transform the object of images into one coordinate system. As a result, registered image would be more informative than original images. Many image processing applications like remote sensing for change detection, estimation of wind speed and direction for weather forecasting, fusion of medical images like PET- MRI, CT-PET etc need image registration. Image registration is a process of aligning two images acquired by same/different sensors, at different times or from different viewpoint. To register images, we need to determine geometric transformation that aligns images with respect to the reference image. The most common
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A FORENSIC ANALYSIS OF IMAGES AND INVESTIGATION MODELS

A FORENSIC ANALYSIS OF IMAGES AND INVESTIGATION MODELS

In this paper we have reviewed the existing literature in the area of digital forensic investigation models and frameworks, with a particular focus on OSN. I had reviewed a comprehensive digital forensic investigation models specifically for OSN that will fulfil the essential requirements of OSN digital forensic investigations. Due to the rapidly approaching changes, the experimental analysis presented in this paper should be updated following the OSN changes in the publication process. There is a need to establish a standardized forensic investigation process for these networks.
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Promoter addresses: revelations from oligonucleotide profiling applied to the Escherichia coli genome

Promoter addresses: revelations from oligonucleotide profiling applied to the Escherichia coli genome

such sequences were taken from all four E.coli genomes (K12, O157:H7, EDL933 and CFT073) to improve statis- tical significance (TATAAT occurred only 128 times in the -100 region of the K12 genome). The results showed that TTGACA is preferred between positions -32 and -27. Fur- ther, it was seen that, with G at -14, the occurrence of TTGACA decreased, (All corresponding data points are highlighted in the Supplementary Information 2 file.) This has been reported by analysis of experimentally char- acterized promoters [22]. These correlations validate the results of oligonucleotide profiling with respect to the sigma 70 binding site.
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Analysis of Imaging Artifacts in MR Brain Images

Analysis of Imaging Artifacts in MR Brain Images

The limitations and malfunction in the hardware or software of the MRI device may cause undesired image distortions, which can lead to misinterpretation of MR brain data. Physiological phenomena artifacts in brain scans are caused by a variety of factors such as respiration, heartbeat, twitching, tremor which affect the quality of MR brain images. Motion artifacts in brain scanning are a chronic problem causing either ghost images or diffuse image noise in the phase-encoding direction 4 .

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Registration and Analysis in Retinal Images for Diagnosis and Monitoring

Registration and Analysis in Retinal Images for Diagnosis and Monitoring

It is important to classify the retinal images into healthy and affected images as to detect diabetic retinopathy. The classifier used is a SVM. SVMs are based on the SRM principle, in contrast to ERM principle in NNs, to minimize the error on the training data. SRMs minimizes a bound on the test error thus allowing SVMs to generalize better. The dataset is trained and then tested n identifies whether the retina is healthy or affected by DR.

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Quality Analysis and Grading of Rice Grain Images

Quality Analysis and Grading of Rice Grain Images

The poor illumination effects were removed from the background and the image is converted to binary image, then successive erosion and dilation operations are performed to separate the touching kernels. By labelling the connected components the grains were counted and area of each connected components is found using region props, the maximum grain length found is used as a structuring element and morphological operations were performed to extract the grains which have length less than the structuring element. Then finally grading formulae is applied which gives the percentage of full length grains in the given sample. The grading formula & standards were acquired from the analysis procedure for grading rice followed in India.
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An investigation into synthesis-by-analysis

An investigation into synthesis-by-analysis

The second method was proposed by Childers et al. (1989). It consists of an algorithm for classifying speech into four categories, silence and speech produced by three different types of excitation; voiced excitation, voiceless excitation and mixed voiced and voiceless excitation. The algorithm consists of a two-channel (speech and EGG) analysis. In this method V-UV classification is performed as described above (Krishnamurthy et al. 1986), while mixed excitation detection is achieved by noting that during mixed voicing the EGG signal appears similar to that of voiced sounds but that the speech signal is small in amplitude and has a high zero level crossing rate. The silence intervals are determined using the fact that the EGG sig­ nal appears as it does with voiceless speech and that the energy in the speech pres­ sure waveform is below a predefined threshold. Childers claims that the algorithm produced correct classification 98.2% of the time as measured against manual classi­ fication. It was noted that a large number of the classification errors occurred due to misclassification of voiceless with mixed frames, errors at the beginning and end of sentences and word boundary errors. If these errors were ignored the performance rose to 99.5%.
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Music Analysis and Synthesis

Music Analysis and Synthesis

for music analysis and synthesis. The first step used for music analysis here is separating the sources and recognizing them. The next step is the estimation of perceptual attributes of music namely pitch, tempo and recognition of notes. Finally using the estimated pitch, tempo and notes recognized, a new audio file is synthesized. This audio file is combined with one or more of the original source audio file(s).

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Texture analysis and synthesis

Texture analysis and synthesis

a Statistical- global statistics measures such as image moments mean, variance, correlations between pixels are used to provide a description of the texture.. Markov or Autoregressive mo[r]

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