Evolution of microstructure and texture in friction stir processed Al-Mg-Mn alloy

Friction stir processing was carried out on the Al-Mg-Mn alloy to achieve ultrafine grained microstructure. The evolution of microstructure and micro-texture was studied in different regions of the deformed sample, namely nugget zone, thermo-mechanically affected zone (TMAZ) and base metal. The average grain sizes of the nugget zone, TMAZ and base metal are 1.5 mu m +/- 0.5 mu m, 15 mu m +/- 8 mu m, and 80 mu m +/- 10 mu m, respectively. The TMAZ exhibits excessive deformation banding structure and sub-grain formation. The orientation gradient within the sub-grain is dependent on grain size, orientation, and distance from nugget zone. The microstructure was partitioned based on the grain orientation spread and grain size values to separate the recrystallized fraction from the deformed region in order to understand the micromechanism of grain refinement. The texture of both deformed and recrystallized regions are similar in nature. Microstructure and texture analysis suggest that the restoration processes are different in different regions of the processed sample. The transition region between nugget zone and TMAZ exhibits large elongated grains surrounded by fine equiaxed grains of different orientation which indicate the process of discontinuous dynamic recrystallization. Within the nugget zone, similar texture between deformed and recrystallized grain fraction suggests that the restoration mechanism is a continuous process.

Effect of substrates and surfactants over the evolution of crystallographic texture of nanostructured ZnO thin films deposited through microwave irradiation

In spite of intense research on ZnO over the past decade, the detailed investigation about the crystallographic texture of as obtained ZnO thin films/coatings, and its deviation with growth surface is scarce. We report a systematic study about the orientation distribution of nanostructured ZnO thin films fabricated by microwave irradiation with the variation of substrates and surfactants. The nanostructured films comprising of ZnO nanorods are grown on semiconductor substrates such as Si(100), Ge(100)], conducting substrates (ITO-coated glass, Cr coated Si), and polymer coated Si (PMMA/Si) to examine the respective development of crystallographic texture. The ZnO deposited on semiconductor substrates yieldsmixed texture, whereas c-axis oriented ZnO nanostructured films are obtained by conducting substrate, and PMMA coated Si substrates. Among all the surfactants, nanostructured film produced by using the lower molecular weight of polymeric surfactants (polyvinylpyrrolidone) shows a stronger (0002) texture, and that can be tuned to (10 - 10) by increasing the molecular weight of the surfactant. The strongest basal pole is achieved for the ZnO deposited on PMMA coated Si as substrate, and cetyl-trimethyl ammonium bromide as cationic surfactant. The texture analysis is carried out by X-ray pole figure analysis using the Schultz reflection method. (C) 2015 Elsevier B.V. All rights reserved.

An FPGA Based Coprocessor for GLCM and Haralick Texture Features and Their Application in Prostate Cancer Classification

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

Automated tumour annotation and analysis for molecular pathology using TissueMark (R)

Objective: Molecular pathology relies on identifying anomalies using PCR or analysis of DNA/RNA. This is important in solid tumours where molecular stratification of patients define targeted treatment. These molecular biomarkers rely on examination of tumour, annotation for possible macro dissection/tumour cell enrichment and the estimation of % tumour. Manually marking up tumour is error prone. Method: We have developed a method for automated tumour mark-up and % cell calculations using image analysis called TissueMark® based on texture analysis for lung, colorectal and breast (cases=245, 100, 100 respectively). Pathologists marked slides for tumour and reviewed the automated analysis. A subset of slides was manually counted for tumour cells to provide a benchmark for automated image analysis. Results: There was a strong concordance between pathological and automated mark-up (100 % acceptance rate for macro-dissection). We also showed a strong concordance between manually/automatic drawn boundaries (median exclusion/inclusion error of 91.70 %/89 %). EGFR mutation analysis was precisely the same for manual and automated annotation-based macrodissection. The annotation accuracy rates in breast and colorectal cancer were 83 and 80 % respectively. Finally, region-based estimations of tumour percentage using image analysis showed significant correlation with actual cell counts. Conclusion: Image analysis can be used for macro-dissection to (i) annotate tissue for tumour and (ii) estimate the % tumour cells and represents an approach to standardising/improving molecular diagnostics.

Texture recognition under varying imaging geometries

La visió és probablement el nostre sentit més dominant a partir del qual derivem la majoria d'informació del món que ens envolta. A través de la visió podem percebre com són les coses, on són i com es mouen. En les imatges que percebem amb el nostre sistema de visió podem extreure'n característiques com el color, la textura i la forma, i gràcies a aquesta informació som capaços de reconèixer objectes fins i tot quan s'observen sota unes condicions totalment diferents. Per exemple, som capaços de distingir un mateix objecte si l'observem des de diferents punts de vista, distància, condicions d'il·luminació, etc. La Visió per Computador intenta emular el sistema de visió humà mitjançant un sistema de captura d'imatges, un ordinador, i un conjunt de programes. L'objectiu desitjat no és altre que desenvolupar un sistema que pugui entendre una imatge d'una manera similar com ho realitzaria una persona. Aquesta tesi es centra en l'anàlisi de la textura per tal de realitzar el reconeixement de superfícies. La motivació principal és resoldre el problema de la classificació de superfícies texturades quan han estat capturades sota diferents condicions, com ara distància de la càmera o direcció de la il·luminació. D'aquesta forma s'aconsegueix reduir els errors de classificació provocats per aquests canvis en les condicions de captura. En aquest treball es presenta detalladament un sistema de reconeixement de textures que ens permet classificar imatges de diferents superfícies capturades en diferents condicions. El sistema proposat es basa en un model 3D de la superfície (que inclou informació de color i forma) obtingut mitjançant la tècnica coneguda com a 4-Source Colour Photometric Stereo (CPS). Aquesta informació és utilitzada posteriorment per un mètode de predicció de textures amb l'objectiu de generar noves imatges 2D de les textures sota unes noves condicions. Aquestes imatges virtuals que es generen seran la base del nostre sistema de reconeixement, ja que seran utilitzades com a models de referència per al nostre classificador de textures. El sistema de reconeixement proposat combina les Matrius de Co-ocurrència per a l'extracció de característiques de textura, amb la utilització del Classificador del veí més proper. Aquest classificador ens permet al mateix temps aproximar la direcció d'il·luminació present en les imatges que s'utilitzen per testejar el sistema de reconeixement. És a dir, serem capaços de predir l'angle d'il·luminació sota el qual han estat capturades les imatges de test. Els resultats obtinguts en els diferents experiments que s'han realitzat demostren la viabilitat del sistema de predicció de textures, així com del sistema de reconeixement.

Texture profile and correlation between sensory and instrumental analyses on extruded snacks

Instrumental texture analysis on extruded snacks is widely applied, however there is no scientific consensus about the test and probe types that can be correlated with the sensory texture of snacks. Eleven commercial extruded snacks of different shapes were evaluated instrumentally using different probes and sensorially through descriptive analysis. The snack texture was described using the attributes of hardness, crispness, adhesiveness, fracturability and chewiness. Cylindrical snacks were described through crispness and fracturability, pelleted and shell-shaped snacks by chewiness and ring-shaped snacks by adhesiveness and hardness. Hardness and adhesiveness were correlated with a Warner-Bratzler test using a V shape probe (r = 0.718 and r = 0.763, respectively), while fracturability and chewiness were correlated with a Warner-Bratzler test using a guillotine (r = 0.776 and r = 0.662, respectively). The fairly strong good correlations enable application of these instrumental tests as an indication of the sensory texture of extruded snacks. © 2013 Elsevier Ltd. All rights reserved.

Texture descriptor based on partially self-avoiding deterministic walker on networks

Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.

Analysis of morphological and functional heterogeneity in ct perfusion images of lung tumours

Questa tesi si propone di innovare lo stato dell’arte dei metodi di analisi dell’eterogeneità in lesioni polmonari attualmente utilizzati, affiancando l’analisi funzionale (emodinamica) a quella morfologica, grazie allo sviluppo di nuove feature specifiche. Grazie alla collaborazione tra il Computer Vision Group (CVG) dell’Università di Bologna e l’Unità Operativa di Radiologia dell’IRCCS-IRST di Meldola (Istituto di Ricovero e Cura a Carattere Scientifico – Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori), è stato possibile analizzare un adeguato numero di casi reali di pazienti affetti da lesioni polmonari primitive, effettuando un’analisi dell’eterogeneità sia su sequenze di immagini TC baseline sia contrast-enhanced, consentendo quindi un confronto tra eterogeneità morfologica e funzionale. I risultati ottenuti sono infine discussi sulla base del confronto con le considerazioni di natura clinica effettuate in cieco da due esperti radiologi dell’IRCCS-IRST.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Experimental investigation of forming limit, void coalescence and crystallographic textures of aluminum alloy 8011 sheet annealed at various temperatures

In this work, a combined forming and fracture limit diagram, fractured void coalescence and texture analysis have been experimentally evaluated for the commercially available aluminum alloy Al 8011 sheet annealed at different temperatures viz. 200 degrees C, 250 degrees C, 300 degrees C and 350 degrees C. The sheets were examined at different annealing temperatures on microstructure, tensile properties, formability and void coalescence. The fractured surfaces of the formed samples were examined using scanning electron microscope (SEM) and these images were correlated with fracture behavior and formability of sheet metals. Formability of Al 8011 was studied and examined at various annealing temperatures using their bulk X-ray crystallographic textures and ODF plots. Forming limit diagrams, void coalescence parameters and crystallographic textures were correlated with normal anisotropy of the sheet metals annealed at different temperatures. (C) 2013 Politechnika Wroclawska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Nano-ZnO particle addition to monolithic magnesium for enhanced tensile and compressive response

In this study, the effects of nanoscale ZnO reinforcement on the room temperature tensile and compressive response of monolithic Mg were studied. Experimental observations indicated strength properties improvement due to nanoscale ZnO addition. A maximum increment in tensile yield strength by similar to 55% and compressive yield strength by 90% (with reduced tension-compression asymmetry) was achieved when 0.8 vol.% ZnO nanoparticles were added to Mg. While the fracture strain values under tensile loads were found to increase significantly (by similar to 95%, in case of Mg-0.48ZnO), it remained largely unaffected under compressive loads. The microstructural characteristics studied in order to comprehend the mechanical response showed significant grain refinement due to grain boundary pinning effect of nano-ZnO particles which resulted in strengthening of Mg. Texture analysis using X-ray and EBSD methods indicated weakening of basal fibre texture in Mg/ZnO nanocomposites which contributed towards the reduction in tension-compression yield asymmetry and enhancement in tensile ductility when compared to pure Mg. (C) 2014 Elsevier B.V. All rights reserved.

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.

Mg/BN nanocomposites: Nano-BN addition for enhanced room temperature tensile and compressive response

The present study elucidates the effects of nanoscale boron nitride particles addition on the microstructural and mechanical characteristics of monolithic magnesium. Novel light-weight Mg nanocomposites containing 0.3, 0.6 and 1.2vol% nano-size boron nitride particulates were synthesized using the disintegrated melt deposition method followed by hot extrusion. Microstructural characterization of developed Mg/x-boron nitride composites revealed significant grain refinement due to the uniform distribution of nano-boron nitride particulates. Texture analysis of selected Mg-1.2 boron nitride nanocomposite showed an increase in the intensity of fiber texture alongside enhanced localized recrystallization when compared to monolithic Mg. Mechanical properties evaluation under indentation, tension and compression loading indicated superior response of Mg/x-boron nitride composites in comparison to pure Mg. The uniform distribution of nanoscale boron nitride particles and the modified crystallographic texture achieved due to the nano-boron nitride addition attributes to the superior mechanical characteristics of Mg/boron nitride nanocomposites.

An integrated aurora image retrieval system: AuroraEye

With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset. (c) 2010 Elsevier Inc. All rights reserved.