Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

Development of a real time Image analysis system for traffic monitoring applications.

Image processing offers unparalleled potential for traffic monitoring and control. For many years engineers have attempted to perfect the art of automatic data abstraction from sequences of video images. This paper outlines a research project undertaken at Napier University by the authors in the field of image processing for automatic traffic analysis. A software based system implementing TRIP algorithms to count cars and measure vehicle speed has been developed by members of the Transport Engineering Research Unit (TERU) at the University. The TRIP algorithm has been ported and evaluated on an IBM PC platform with a view to hardware implementation of the pre-processing routines required for vehicle detection. Results show that a software based traffic counting system is realisable for single window processing. Due to the high volume of data required to be processed for full frames or multiple lanes, system operations in real time are limited. Therefore specific hardware is required to be designed. The paper outlines a hardware design for implementation of inter-frame and background differencing, background updating and shadow removal techniques. Preliminary results showing the processing time and counting accuracy for the routines implemented in software are presented and a real time hardware pre-processing architecture is described.

A new technique to automatically quantify microstructures of fine grained carbonate mylonites: two-step etching combined with SEM imaging and image analysis

A two-step etching technique for fine-grained calcite mylonites using 0.37% hydrochloric and 0.1% acetic acid produces a topographic relief which reflects the grain boundary geometry. With this technique, calcite grain boundaries become more intensely dissolved than their grain interiors but second phase minerals like dolomite, quartz, feldspars, apatite, hematite and pyrite are not affected by the acid and therefore form topographic peaks. Based on digital backscatter electron images and element distribution maps acquired on a scanning electron microscope, the geometry of calcite and the second phase minerals can be automatically quantified using image analysis software. For research on fine-grained carbonate rocks (e.g. dolomite calcite mixtures), this low-cost approach is an attractive alternative to the generation of manual grain boundary maps based on photographs from ultra-thin sections or orientation contrast images.

Digital image processing techniques for pavement macro-texture analysis

Road surface macro-texture is an indicator used to determine the skid resistance levels in pavements. Existing methods of quantifying macro-texture include the sand patch test and the laser profilometer. These methods utilise the 3D information of the pavement surface to extract the average texture depth. Recently, interest in image processing techniques as a quantifier of macro-texture has arisen, mainly using the Fast Fourier Transform (FFT). This paper reviews the FFT method, and then proposes two new methods, one using the autocorrelation function and the other using wavelets. The methods are tested on pictures obtained from a pavement surface extending more than 2km's. About 200 images were acquired from the surface at approx. 10m intervals from a height 80cm above ground. The results obtained from image analysis methods using the FFT, the autocorrelation function and wavelets are compared with sensor measured texture depth (SMTD) data obtained from the same paved surface. The results indicate that coefficients of determination (R2) exceeding 0.8 are obtained when up to 10% of outliers are removed.

Porohyperelastic analysis of single osteocyte using AFM and inverse FEA

Osteocytes are the mature cells and perform as mechanosensors within the bone. The mechanical property of osteocytes plays an important role to fulfill these functions. However, little researches have been done to investigate the mechanical deformation properties of single osteocytes. Atomic Force Microscopy (AFM) is a state-of-art experimental facility for high resolution imaging of tissues, cells and any surfaces as well as for probing mechanical properties of the samples both qualitatively and quantitatively. In this paper, the experimental study based on AFM is firstly used to obtain forceindentation curves of single round osteocytes. The porohyperelastic (PHE) model of a single osteocyte is then developed by using the inverse finite element analysis (FEA) to identify and extract mechanical properties from the experiment results. It has been found that the PHE model is a good candidature for biomechanics studies of osteocytes.

Porohyperelastic analysis of single chondrocyte using AFM and inverse FEA

The aim of this paper is to determine the creep and relaxation responses of single chondrocytes in vitro. Firstly, Atomic Force Microscopy (AFM) was used to obtain the force-indentation curves of single chondrocytes at the strain-rate of 7.05 s-1. This result was then employed in inverse finite element analysis (FEA) using porohyperelastic (PHE) idealization of the cells to determine their mechanical properties. The PHE model results agreed well with AFM experimental data. This PHE model was then utilized to study chondrocyte’s creep and relaxation behaviors. The results revealed that the effect of fluid was predominant for cell’s mechanical behaviors and that the PHE is a good model for biomechanics studies of chondrocytes.

Microstructural analysis of non-woven fabrics using scanning electron microscopy and image processing. Part 1:Development and verification of the methods

This paper reports image analysis methods that have been developed to study the microstructural changes of non-wovens made by the hydroentanglement process. The validity of the image processing techniques has been ascertained by applying them to test images with known properties. The parameters in preprocessing of the scanning electron microscope (SEM) images used in image processing have been tested and optimized. The fibre orientation distribution is estimated using fast Fourier transform (FFT) and Hough transform (HT) methods. The results obtained using these two methods are in good agreement. The HT method is more demanding in computational time compared with the Fourier transform (FT) method. However, the advantage of the HT method is that the actual orientation of the lines can be concluded directly from the result of the transform without the need for any further computation. The distribution of the length of the straight fibre segments of the fabrics is evaluated by the HT method. The effect of curl of the fibres on the result of this evaluation is shown.

Microstructural analysis of non-woven fabrics using scanning electron microscopy and image processing. Part 2:Application to hydroentangled fabrics

The image analysis techniques developed in Part 1 to study microstructural changes in non-woven fabrics are applied to measure the fibre orientation distribution and fibre length distribution of hydroentangled fabrics. The results are supported by strength and modulus measurements using samples from the same fabrics. It is shown that the techniques developed can successfully be used to assess the degree of entanglement of hydroentangled fabrics regardless of their thickness.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Quantitative fractography by digital image processing: NIH Image macro tools for stereo pair analysis and 3-D reconstruction

A set of NIH Image macro programs was developed to make qualitative and quantitative analyses from digital stereo pictures produced by scanning electron microscopes. These tools were designed for image alignment, anaglyph representation, animation, reconstruction of true elevation surfaces, reconstruction of elevation profiles, true-scale elevation mapping and, for the quantitative approach, surface area and roughness calculations. Limitations on time processing, scanning techniques and programming concepts are also discussed.

Quantitative analysis of photodynamic therapy effects in rat mammary tumor vascular density using image-pro plus software

Photodynamic therapy (PDT) is a treatment modality that has advanced rapidly in recent years. It causes tissue and vascular damage with the interaction of a photosensitizing agent (PS), light of a proper wavelength, and molecular oxygen. Evaluation of vessel damage usually relies on histopathology evaluation. Results are often qualitative or at best semi-quantitative based on a subjective system. The aim of this study was to evaluate, using CD31 immunohistochem- istry and image analysis software, the vascular damage after PDT in a well-established rodent model of chemically induced mammary tumor. Fourteen Sprague-Dawley rats received a single dose of 7,12-dimethylbenz(a)anthraxcene (80 mg/kg by gavage), treatment efficacy was evaluated by comparing the vascular density of tumors after treatment with Photogem® as a PS, intraperitoneally, followed by interstitial fiber optic lighting, from a diode laser, at 200 mW/cm and light dose of 100 J/cm directed against his tumor (7 animals), with a control group (6 animals, no PDT). The animals were euthanized 30 hours after the lighting and mammary tumors were removed and samples from each lesion were formalin-fixed. Immunostained blood vessels were quantified by Image Pro-Plus version 7.0. The control group had an average of 3368.6 ± 4027.1 pixels per picture and the treated group had an average of 779 ± 1242.6 pixels per area (P < 0.01), indicating that PDT caused a significant decrease in vascular density of mammary tumors. The combined immu- nohistochemistry using CD31, with selection of representative areas by a trained pathology, followed by quantification of staining using Image Pro-Plus version 7.0 system was a practical and robust methodology for vessel damage evalua- tion, which probably could be used to assess other antiangiogenic treatments.

Structural analysis of a UAV wing through image processing and FEM

Analisi strutturale dell’ala di un UAV (velivolo senza pilota a bordo), sviluppata usando varie metodologie: misurazioni sperimentali statiche e dinamiche, e simulazioni numeriche con l’utilizzo di programmi agli elementi finiti. L’analisi statica è stata a sua volta portata avanti seguendo due differenti metodi: la classica e diretta determinazione degli spostamenti mediante l’utilizzo di un catetometro e un metodo visivo, basato sull’elaborazione di immagini e sviluppato appositamente a tale scopo in ambiente Matlab. Oltre a ciò è stata svolta anche una analisi FEM volta a valutare l’errore che si ottiene affrontando il problema con uno studio numerico. Su tale modello FEM è stata svolta anche una analisi di tipo dinamico con lo scopo di confrontare tali dati con i dati derivanti da un test dinamico sperimentale per ottenere informazioni utili per una seguente possibile analisi aeroelastica.