Processing mesh animations: from static to dynamic geometry and back

Static triangle meshes are the representation of choice for artificial objects, as well as for digital replicas of real objects. They have proven themselves to be a solid foundation for further processing. Although triangle meshes are handy in general, it may seem that their discrete approximation of reality is a downside. But in fact, the opposite is true. The approximation of the real object's shape remains the same, even if we willfully change the vertex positions in the mesh, which allows us to optimize it in this way. Due to modern acquisition methods, such a step is always beneficial, often even required, prior to further processing of the acquired triangle mesh. Therefore, we present a general framework for optimizing surface meshes with respect to various target criteria. Because of the simplicity and efficiency of the setup it can be adapted to a variety of applications. Although this framework was initially designed for single static meshes, the application to a set of meshes is straightforward. For example, we convert a set of meshes into compatible ones and use them as basis for creating dynamic geometry. Consequently, we propose an interpolation method which is able to produce visually plausible interpolation results, even if the compatible input meshes differ by large rotations. The method can be applied to any number of input vertex configurations and due to the utilization of a hierarchical scheme, the approach is fast and can be used for very large meshes. Furthermore, we consider the opposite direction. Given an animation sequence, we propose a pre-processing algorithm that considerably reduces the number of meshes required to describe the sequence, thus yielding a compact representation. Our method is based on a clustering and classification approach, which can be utilized to automatically find the most prominent meshes of the sequence. The original meshes can then be expressed as linear combinations of these few representative meshes with only small approximation errors. Finally, we investigate the shape space spanned by those few meshes and show how to apply different interpolation schemes to create other shape spaces, which are not based on vertex coordinates. We conclude with a careful analysis of these shape spaces and their usability for a compact representation of an animation sequence

An Efficient Dorsal Hand Vein Recognition Based on Firefly Algorithm

Biometric technology is an efficient personal authentication andidentification technique. As one of the main-stream branches, dorsal handvein recognition has been recently attracted the attention of researchers. It is more preferable than the other types of biometrics becuse it’s impossible to steal or counterfeit the patterns and the pattern of the vessels of back of the hand is fixed and unique with repeatable biometric features. Also, the recent researches have been obtained no certain recognition rate yet becuse of the noises in the imaging patterns, and impossibility of Dimension reducing because of the non-complexity of the models, and proof of correctness of identification is required. Therefore, in this paper, first, the images of blood vessels on back of the hands of people is analysed, and after pre-processing of images and feature extraction (in the intersection between the vessels) we began to identify people using firefly clustering algorithms. This identification is done based on the distance patterns between crossing vessels and their matching place. The identification will be done based on the classification of each part of NCUT data set and it consisting of 2040 dorsal hand vein images. High speed in patterns recognition and less computation are the advantages of this method. The recognition rate of this method ismore accurate and the error is less than one percent. At the end thecorrectness percentage of this method (CLU-D-F-A) for identification iscompared with other various algorithms, and the superiority of the proposed method is proved.DOI:http://dx.doi.org/10.11591/ijece.v3i1.176

Image processing for plastic surgery planning

This thesis presents some image processing tools for plastic surgery planning. In particular, it presents a novel method that combines local and global context in a probabilistic relaxation framework to identify cephalometric landmarks used in Maxillofacial plastic surgery. It also uses a method that utilises global and local symmetry to identify abnormalities in CT frontal images of the human body. The proposed methodologies are evaluated with the help of several clinical data supplied by collaborating plastic surgeons

Screening soybean for adaptation to relay intercropping systems: associations between reproductive organ abscission and yield

The flower and pod abscission is one of the characteristics of soybean that severely limits yield, especially when intercropped with maize. Therefore, suitable soybean cultivars for intercropping are urgently needed to improve farmland productivity. We conducted a two-year field experiment to evaluate the flower and pod abscission, dry matter production, and yield advantages of 15 soybean cultivars. The results of the principal component analysis (PCA) and cluster analysis (CA) showed that 15 soybean cultivars were classified into three groups, i.e., high-yielding group (HYG), mid-yielding cultivars (MYG), and low-yielding cultivars (LYG). In the HYG group, ND12 and GX3 had characteristics of more flowers and pods and less abscission of flowers and pods. Moreover, the net assimilation rate (NAR) and relative growth rate (RGR) of HYG were significantly higher than the other. The HYG obtained a considerably higher partition ratio of 53% from biomass to seed than the other. Therefore, selecting and breeding cultivars with the characteristics of more flowers and pods and less abscission of flowers and pods can help to increase soybean yield in intercropping.This research was funded by the Program on Industrial Technology System of National Soybean (CARS-04-PS18), and the National Key Research and Development Program of China (2021YFF1000500). Qing Du was a recipient of a joint PhD scholarship supported by the China Scholarship Council (CSC) (No. 202106910037)

Medium-term response of breeding Blue Chaffinch Fringilla teydea teydea to experimental thinning in a Pinus canariensis plantation (Tenerife, Canary Islands)

We studied the medium-term response of the endemic Blue Chaffinch Fringilla teydea teydea to experimental thinning in a Pinus canariensis plantation on the island of Tenerife during breeding season. Distance Sampling method was applied to line transects, and habitat preferences were modelled by means of univariate regression trees. The density was 1.70 birds/ha (1.09 to 2.68 95%CI) in thinned areas and 0.56 birds/ha (0.33 to 0.97 95%CI) in unthinned areas. The Blue Chaffinch densities peaked in thinned areas where the density of trees with Diameter at Breast Height of <25 cmwas between 10.5 and 16.5 trees/plot (r = 25 m) and the cover of Adenocarpus shrubs was 82.5%. Thinning had added heterogeneity into the stand structure at least in terms of lowering the basal area of small pine trees and increasing the understorey cover of Adenocarpus shrubs, with average cover being 37.15% in thinned and only 1.40% in unthinned areas.Our results justify the silvicultural thinning of 2844 hectares of pine plantation on the summit of Gran Canaria as a means of increasing the density of the endangered Gran Canaria Blue Chaffinch (Fringilla teydea polatzeki)

The Dark Energy Survey

We describe the Dark Energy Survey (DES), a proposed optical-near infrared survey of 5000 sq. deg of the South Galactic Cap to ~24th magnitude in SDSS griz, that would use a new 3 sq. deg CCD camera to be mounted on the Blanco 4-m telescope at Cerro Telolo Inter-American Observatory (CTIO). The survey data will allow us to measure the dark energy and dark matter densities and the dark energy equation of state through four independent methods: galaxy clusters, weak gravitational lensing tomography, galaxy angular clustering, and supernova distances. These methods are doubly complementary: they constrain different combinations of cosmological model parameters and are subject to different systematic errors. By deriving the four sets of measurements from the same data set with a common analysis framework, we will obtain important cross checks of the systematic errors and thereby make a substantial and robust advance in the precision of dark energy measurements.Comment: White Paper submitted to the Dark Energy Task Force, 42 page

An intelligent framework for pre-processing ancient Thai manuscripts on palm leaves

In Thailand’s early history, prior to the availability of paper and printing technologies, palm leaves were used to record information written by hand. These ancient documents contain invaluable knowledge. By digitising the manuscripts, the content can be preserved and made widely available to the interested community via electronic media. However, the content is difficult to access or retrieve. In order to extract relevant information from the document images efficiently, each step of the process requires reduction of irrelevant data such as noise or interference on the images. The pre-processing techniques serve the purpose of extracting regions of interest, reducing noise from the image and degrading the irrelevant background. The image can then be directly and efficiently processed for feature selection and extraction prior to the subsequent phase of character recognition. It is therefore the main objective of this study to develop an efficient and intelligent image preprocessing system that could be used to extract components from ancient manuscripts for information extraction and retrieval purposes. The main contributions of this thesis are the provision and enhancement of the region of interest by using an intelligent approach for the pre-processing of ancient Thai manuscripts on palm leaves and a detailed examination of the preprocessing techniques for palm leaf manuscripts. As noise reduction and binarisation are involved in the first step of pre-processing to eliminate noise and background from image documents, it is necessary for this step to provide a good quality output; otherwise, the accuracy of the subsequent stages will be affected. In this work, an intelligent approach to eliminate background was proposed and carried out by a selection of appropriate binarisation techniques using SVM. As there could be multiple binarisation techniques of choice, another approach was proposed to eliminate the background in this study in order to generate an optimal binarised image. The proposal is an ensemble architecture based on the majority vote scheme utilising local neighbouring information around a pixel of interest. To extract text from that binarised image, line segmentation was then applied based on the partial projection method as this method provides good results with slant texts and connected components. To improve the quality of the partial projection method, an Adaptive Partial Projection (APP) method was proposed. This technique adjusts the size of a character strip automatically by adapting the width of the strip to separate the connected component of consecutive lines through divide and conquer, and analysing the upper vowels and lower vowels of the text line. Finally, character segmentation was proposed using a hierarchical segmentation technique based on a contour-tracing algorithm. Touching components identified from the previous step were then separated by a trace of the background skeletons, and a combined method of segmentation. The key datasets used in this study are images provided by the Project for Palm Leaf Preservation, Northeastern Thailand Division, and benchmark datasets from the Document Image Binarisation Contest (DIBCO) series are used to compare the results of this work against other binarisation techniques. The experimental results have shown that the proposed methods in this study provide superior performance and will be used to support subsequent processing of the Thai ancient palm leaf documents. It is expected that the contributions from this study will also benefit research work on ancient manuscripts in other languages

Detecting wide lines using isotropic nonlinear filtering

2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Improvements in Scanning Infrared Thermography

Non-destructive evaluation techniques are important for many industries. Scanning infrared thermography systems have the potential to analyze materials and parts, quickly, accurately, and at a reduced cost compared to other systems. Scanning infrared thermography uses Fourier's law of conductive heat transfer to detect both material and geometric anomalies in a particular sample. The current system has been developed to create an easy to operate physical system and an interface utilizing commercial software packages. New hardware components have been designed to work in concert with specially developed analytical models to treat surfaces with changing emissivity and uniformly finished surfaces like those used in traditional infrared scanning systems.A newly developed LabView program has simplified the data collection process by combining all data analysis into a single program. The program uses radiative heat transfer theory and incorporates temperature data from several sources to calculate the true surface temperature of the sample which is crucial for defect detection. An improved camera shroud has also improved the ability to handle variable emissivity surfaces.Several computational models have been developed to determine the defect detection resolution of a variety of defects using this system. Results obtained from the models showed that the system is capable of detecting crack defects as small as 0.5 cm in lateral length. Void defects and other 3-dimensional defects were shown to be marginally detectable as well. Radiative heat transfer analysis was performed on the camera shroud and it was determined that the camera shroud has little effect on the radiation received by the camera.The system has been successful at detecting defects on coated surfaces where cracks were oriented parallel to the heating element and at sub-optimal angles. In addition, new experimentation has shown the new camera shroud and LabView program to be successful at removing reflected radiation from variable emissivity, diffuse surfaces. However, the system has only been marginally successful at removing artifacts of reflected radiation from thermographic images of surfaces that show a high degree of specularity, making temperature correction and crack detection difficult.The system has also been used to test non-metallic samples to determine whether it would be a viable choice for applications in this area. A set of composite samples was tested to verify whether defects in this type of material could be successfully detected. Testing showed that sub-surface changes in thermal-conductivity could be detected using the current system. However, due to the extremely low thermal conductivities of some of the materials, testing proved to be much more time consuming and less successful than it is with metal samples. For thin sheets, delaminations and other sub-surface defects may prove difficult to detect