Robust Circle Detection

International audienceIn this paper we present a method of robustly detect circles in a line drawing image. The method is fast, robust and very reliable, and is capable of assessing the quality of its detection. It is based on Random Sample Consensus minimization, and uses techniques that are inspired from object tracking in image sequences

Natural Resources Policy Under the Bush Administration: Not What it Says, But What it has Done in Court

Bioassays relying on magnetic read-out using probe-tagged magnetic nanobeads are potential platforms for low-cost biodiagnostic devices for pathogen detection. For optimal assay performance it is crucial to apply an easy, efficient and robust bead-probe conjugation protocol. In this paper, sensitive (1.5 pM) singleplex detection of bacterial DNA sequences is demonstrated in a portable AC susceptometer by a magnetic nanobead-based bioassay principle; the volume-amplified magnetic nanobead detection assay (VAM-NDA). Two bead sizes, 100 and 250 nm, are investigated along with a highly efficient, rapid, robust, and stable conjugation chemistry relying on the avidin-biotin interaction for bead-probe attachment. Avidin-biotin conjugation gives easy control of the number of detection probes per bead; thus allowing for systematic investigation of the impact of varying the detection probe surface coverage upon bead immobilization in rolling circle amplified DNA-coils. The existence of an optimal surface coverage is discussed. Biplex VAM-NDA detection is for the first time demonstrated in the susceptometer: Semi-quantitative results are obtained and it is concluded that the concentration of DNA-coils in the incubation volume is of crucial importance for target quantification. The present findings bring the development of commercial biodiagnostic devices relying on the VAM-NDA further towards implementation in point-of-care and outpatient settings

CircleSnake: Instance Segmentation with Circle Representation

Circle representation has recently been introduced as a medical imaging optimized representation for more effective instance object detection on ball-shaped medical objects. With its superior performance on instance detection, it is appealing to extend the circle representation to instance medical object segmentation. In this work, we propose CircleSnake, a simple end-to-end circle contour deformation-based segmentation method for ball-shaped medical objects. Compared to the prevalent DeepSnake method, our contribution is three-fold: (1) We replace the complicated bounding box to octagon contour transformation with a computation-free and consistent bounding circle to circle contour adaption for segmenting ball-shaped medical objects; (2) Circle representation has fewer degrees of freedom (DoF=2) as compared with the octagon representation (DoF=8), thus yielding a more robust segmentation performance and better rotation consistency; (3) To the best of our knowledge, the proposed CircleSnake method is the first end-to-end circle representation deep segmentation pipeline method with consistent circle detection, circle contour proposal, and circular convolution. The key innovation is to integrate the circular graph convolution with circle detection into an end-to-end instance segmentation framework, enabled by the proposed simple and consistent circle contour representation. Glomeruli are used to evaluate the performance of the benchmarks. From the results, CircleSnake increases the average precision of glomerular detection from 0.559 to 0.614. The Dice score increased from 0.804 to 0.849. The code has been released: https://github.com/hrlblab/CircleSnakeComment: Machine Learning in Medical Imaging Workshop for 2022 MICCA

Efficient and robust analysis of complex scattering data under noise in microwave resonators

Superconducting microwave resonators are reliable circuits widely used for detection and as test devices for material research. A reliable determination of their external and internal quality factors is crucial for many modern applications, which either require fast measurements or operate in the single photon regime with small signal to noise ratios. Here, we use the circle fit technique with diameter correction and provide a step by step guide for implementing an algorithm for robust fitting and calibration of complex resonator scattering data in the presence of noise. The speedup and robustness of the analysis are achieved by employing an algebraic rather than an iterative fit technique for the resonance circle

Real Time Face-Tracking And Iris Localization

Robust, non-intrusive human eye detection problem has been a fundamental and challenging problem for computer vision area. Not only it is a problem of its own, it can be used to ease the problem of finding the locations of other facial features for recognition tasks and human-computer interaction purposes as well. Many previous works have the capability of determining the locations of the human eyes but the main task in this thesis is not only a vision system with eye detection capability. Our aim is to design a real-time, robust, scale-invariant face tracker system with human eye movement indication property using the movements of iris based on localization technique indicate from image processing and circle fitting technique. As a result, our eye tracker system was successfully implemented using non-intrusive webcam with less error

Real-time eye tracking and iris localization

Robust, non-intrusive human eye detection problem has been a fundamental and challenging problem for computer vision area. Not only it is a problem of its own, it can be used to ease the problem of finding the locations of other facial features for recognition tasks and human-computer interaction purposes as well. Many previous works have the capability of determining the locations of the human eyes but the main task in this paper is not only a vision system with eye detection capability.Our aim is to design a real-time face tracker system and iris localization using edge point detection method indicates from image processing and circle fitting technique. As a result, our eye tracker system was successfully implemented using non-intrusive webcam with less error