Algorithms for Shape Analysis of Contours and Waveforms

In this paper we present a new shape analysis algorithm. The key distinguishing aspect of our algorithm is that it is completely compositional, bottom-up and non-iterative. We present our algorithm as an inference system for computing Hoare triples summarizing heap manipulating programs. Our inference rules are compositional: Hoare triples for a compound statement are computed from the Hoare triples of its component statements. These inference rules are used as the basis for a bottom-up shape analysis of programs.Specifically, we present a logic of iterated separation formula (LISF) which uses the iterated separating conjunct of Reynolds [17] to represent program states. A key ingredient of our inference rules is a strong bi-abduction operation between two logical formulas. We describe sound strong bi-abduction and satisfiability decision procedures for LISF.We have built a prototype tool that implements these inference rules and have evaluated it on standard shape analysis benchmark programs. Preliminary results show that our tool can generate expressive summaries, which are complete functional specifications in many cases.KeywordsModel CheckInference RuleAuxiliary VariableShape AnalysisCompose RuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Reliable banknote recognition is critical for detecting counterfeit banknotes in ATMs and help visual impaired people. To solve this problem, it was implemented a computer vision system that can recognize multiple banknotes in different perspective views and scales, even when they are within cluttered environments in which the lighting conditions may vary considerably. The system is also able to recognize banknotes that are partially visible, folded, wrinkled or even worn by usage. To accomplish this task, the system relies on computer vision algorithms, such as image preprocessing, feature detection, description and matching. To improve the confidence of the banknote recognition the feature matching results are used to compute the contour of the banknotes using an homography that later on is validated using shape analysis algorithms. The system successfully recognized all Euro banknotes in 80 test images even when there were several overlapping banknotes in the same test image.

Algorithms for pulse shape analysis using silicon detectors

Diagnostic performance of McMaster, Wisconsin, and automated egg counting techniques for enumeration of equine strongyle eggs in fecal samples

I propose novel 3D shape analysis and modeling algorithm for active contours using variational scheme. The proposed algorithm utilizes an unknown surface of 3D shape by normal to 3D shape analysis and modeling. It would be used to get high quality reconstruction's results from many dimensions' data. I give it by utilizing continuous anisotropism weights would finish comparable ameliorate to surface reconstruction.

Gamma-ray imaging techniques, such as Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), are becoming increasingly important for clinical diagnosis. As the power of these methods becomes more evident, the use of these techniques is becoming more widespread However, the performance of existing systems is restricted by the inherent properties of the scintillator detectors they are based on (e.g. poor energy resolution). The development of High Purity Germanium detectors has now reached the stage where they can be used as effective imaging devices. The electrical segmentation of the Germanium crystal coupled with digital signal processing electronics allows the measurement of energy, time, and position following the interaction of a gamma-ray. We propose to build a PET imaging system composed of two segmented planar HPGe detectors. The position and energy information are extracted following the digitisation of the detector charge signal, analysed using Pulse Shape Analysis (PSA) algorithms. Such a technique can potentially give a position resolution of about 1 mm/sup 3/ inside the detector volume. A prototype of a Compton camera has been built in order to test our pulse processing techniques and develop some gamma-ray tracking algorithms. The system is composed of a planar detector with 5mm strips in a 24/spl times/12 configuration, and a 16 segment coaxial Clover detector. Before being able to reconstruct the path of gamma-rays with the camera, it is necessary to calibrate the response of each detector as a function of the position. Several characterisation measurements have been made using an automated detector scanning systems. Preliminary results from the characterisation of the Clover will are presented in this paper.

SEM Metrology becomes the standard metrology for the mask industry, as the precision and accuracy requirements tighten continuously. At the same time, analysis of general shape features becomes an important task in wafer metrology. In this paper we consider the basic requirements and suggested implementations for performing 2D metrology on reticles and wafers, [i.e. measurements of OPC (Optical Proximity Correction) structures, End of Lines, Dual Damascene and Corner Rounding]. The authors consider the following challenges related to the development of a generic algorithm for general shape 2D analysis: (1) A generic segmentation of the feature. It should be robust to noise, as well as brightness and contrast changes. (2) The complexity of two dimensional general shape features metrology. Standard CD SEM metrology is based on metrics describing simple geometric shapes such as ellipses and lines). (3) Obtaining such metrics that can be used as handles for process control (i.e. what to measure on the 2D feature). In the first part of the paper we describe a novel algorithm for segmentation and geometric analysis of general shape features based on a Smoothing Spline and the methods of differential geometry. Next, we consider the numerical methods implemented for shape analysis of noisy contours. In the second part of the paper the performance of our methods on synthetic contours of circular arc with different noise levels is demonstrated. We conclude with sample results of several suggested metrics measured on real SEM images of reticles and wafers.

This paper develops an approach based on wavelet transform for the evaluation of harmonic contents of power system waveforms. The new algorithm can simultaneously identify all harmonics including integer, noninteger and subharmonics. In the first step of the approach, the frequency spectrum of the waveform is decomposed into subbands using discrete wavelet packet transform filter banks. In the second step, continuous wavelet transform is applied to nonzero subbands to evaluate the harmonic contents. In the first step, there is the problem of images due to down samplings and up samplings of the waveform. A method for alleviating this image problem is developed in the paper. Methods are developed to accurately quantify harmonics frequency amplitude and phase. The approach is validated by its application to synthesised waveforms and to power system waveforms measured in the Western Australia system. It is found to be powerful and suitable for practical use.

Shape Analysis is concerned with determining invariants, i.e. structural properties of the heap, for programs that manipulate pointers and heap-allocated storage. Recently, very precise shape analysis algorithms have been developed that are able to prove the partial correctness of heap-manipulating programs. We explore the use of shape analysis to analyze abstract data types (ADTs). The ADT Set shall serve as an example, as it is widely used and can be found in most of the major data type libraries, like STL, the Java API, or LEDA. We formalize our notion of the ADT Set by algebraic specification. Two prototypical C set implementations are presented, one based on lists, the other on trees. We instantiate a parametric shape analysis framework to generate analyses that are able to prove the compliance of the two implementations to their specification.

The evolution of human-computer interaction (HCI) has led to the emergence of more natural, intuitive methods of control, especially in the domain of gaming. Traditional input devices such as keyboards, mice, and joysticks, though reliable, can limit user immersion and interactivity. This project presents a novel hand gesture-based virtual driving simulator that utilizes Open-CV to detect and interpret real-time hand gestures, thereby offering an innovative and engaging alternative to conventional control mechanisms in driving games. The proposed system employs a standard webcam to capture live video input of the user’s hand gestures. Using a combination of computer vision techniques such as contour analysis and convex hull algorithms the system accurately identifies gestures corresponding to steering, acceleration, and braking. These recognized gestures are then mapped to simulated keyboard events, enabling control of a wide range of commercially available driving games. By eliminating the need for additional hardware, the system offers an affordable and accessible solution for enhancing user experience. Experimental results demonstrate the system’s efficiency, achieving over 90% accuracy in gesture recognition and maintaining a response latency under 100 milliseconds, thereby ensuring smooth gameplay. The system was successfully tested with multiple racing simulators, receiving positive feedback from users who appreciated its intuitive and immersive nature. This project not only showcases the potential of vision-based gesture recognition in gaming but also sets a foundation for future enhancements involving complex gesture sets and virtual reality (VR) integration.

We present in this paper the application of mathematical morphology operators through a transformation of the Cartesian image into another geometric space, i.e. pol-log image. The conversion into polar-logarithmic coordinates as well as the derived cyclic morphology provides satisfying results in image analysis applied to round objects or spheroid-shaped 3D-object models. As an example of application, an algorithm for the shape analysis of the shape of red blood cells is given.

This work presents a new approach and an algorithm for binary image representation, which is applied for the fast and efficient computation of moments on binary images. This binary image representation scheme is called image block representation, since it represents the image as a set of nonoverlapping rectangular areas. The main purpose of the image block representation process is to provide an efficient binary image representation rather than the compression of the image. The block represented binary image is well suited for fast implementation of various processing and analysis algorithms in a digital computing machine. The two-dimensional (2-D) statistical moments of the image may be used for image processing and analysis applications. A number of powerful shape analysis methods based on statistical moments have been presented, but they suffer from the drawback of high computational cost. The real-time computation of moments in block represented images is achieved by exploiting the rectangular structure of the blocks.

This paper aims to examine the validity of digital volume pulse waveform index namely the diastolic pulse peak (Dpp) in the evaluation of type II diabetics. In total, 153 participants (115 healthy participants and 48 diabetics type II patients) are recruited during the study. A customized algorithm for DVP waveform analysis is developed in MATLAB to analyze and calculate Dpp and b/a indices. The b/a index is found to be negatively correlated with both age and HbA1C test (\(r=-83.8\) and \(r=-66.7\), respectively), while Dpp index is found to be positively correlated with age and HbA1C test (\(r=65.7\) and \(r= 63.3\), respectively). The DVP's Dpp index showed strong association with age and HbA1C test since it remains statistically significant based on the analysis of multi-linear regression. The model revealed that b/a, age, and Dpp contribute by 71.9\% of the variance in HbA1C test. The findings showed that age, b/a, and Dpp indices are promising factors in diabetes type II assessment. These findings expand the potential utility of DVP signal in clinical settings.

The T-Line(®) system (Tensys(®) Medical Inc., San Diego, CA, USA) non-invasively estimates cardiac output (CO) using autocalibrating pulse contour analysis of the radial artery applanation tonometry-derived arterial waveform. We compared T-Line CO measurements (TL-CO) with invasively obtained CO measurements using transpulmonary thermodilution (TDCO) and calibrated pulse contour analysis (PC-CO) in patients after major gastrointestinal surgery. We compared 1) TL-CO versus TD-CO and 2) TL-CO versus PC-CO in 27 patients treated in the intensive care unit (ICU) after major gastrointestinal surgery. For the assessment of TD-CO and PC-CO we used the PiCCO(®) system (Pulsion Medical Systems SE, Feldkirchen, Germany). Per patient, we compared two sets of TD-CO and 30 minutes of PC-CO measurements with the simultaneously recorded TL-CO values using Bland-Altman analysis. The mean of differences (± standard deviation; 95% limits of agreement) between TL-CO and TD-CO was -0.8 (±1.6; -4.0 to +2.3) l/minute with a percentage error of 45%. For TL-CO versus PC-CO, we observed a mean of differences of -0.4 (±1.5; -3.4 to +2.5) l/minute with a percentage error of 43%. In ICU patients after major gastrointestinal surgery, continuous non-invasive CO measurement based on autocalibrating pulse contour analysis of the radial artery applanation tonometry-derived arterial waveform (TL-CO) is feasible in a clinical study setting. However, the agreement of TL-CO with TD-CO and PC-CO observed in our study indicates that further improvements are needed before the technology can be recommended for clinical use in these patients.

In this article we shall present a unified and axiomatized view of several theories and algorithms of image multiscale analysis (and low level vision) which have been developed in the past twenty years. We shall show that under reasonable invariance and assumptions, all image (and shape) analyses can be reduced to a single partial differential equation. In the same way, movie analysis leads to a single parabolic differential equation. We discuss some applications to image segmentation and movie restoration. The experiments show how accurate and invariant the numerical schemes must be and we compare several (old and new) algorithms by discussing how well they match the axiomatic invariance requirements.