Search results for "Thresholding"
showing 10 items of 47 documents
Reproducibility and accuracy in the morphometric and mechanical quantification of trabecular bone from 3Tesla magnetic resonance images
2014
Abstract Objective We used an animal model to analyze the reproducibility and accuracy of certain biomarkers of bone image quality in comparison to a gold standard of computed microtomography (μCT). Materials and methods We used magnetic resonance (MR) imaging and μCT to study the metaphyses of 5 sheep tibiae. The MR images (3 T) were acquired with a T1-weighted gradient echo sequence and an isotropic spatial resolution of 180 μm. The μCT images were acquired using a scanner with a spatial resolution of 7.5 μm isotropic voxels. In the preparation of the images, we applied equalization, interpolation, and thresholding algorithms. In the quantitative analysis, we calculated the percentage of …
A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault
2020
This paper proposes a smart sensing method for real-time monitoring of low voltage series arc fault. It is based on the wavelet coefficient mean-difference algorithm and the four spikes appearing within two fundamental periods criterion with adaptive threshold. The method also uses the hard thresholding wavelet denoising with the universal threshold. An arc fault factor and a load adaptation factor are introduced and combined with a correction factor, so allowing the selection of the adaptive threshold in real-time and the series arc fault detection.
Proba-V cloud detection Round Robin: Validation results and recommendations
2017
This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Prob…
Automatische Berechnung des Milzvolumens aus Spiral-CT-Daten mit Hilfe neuronaler Netze und „Fuzzy Logik”∗
2000
PURPOSE To assess spleen segmentation and volumentry in spiral CT scans with and without pathological changes of splenic tissue. METHODS The image analysis software HYBRIKON is based on region growing, self-organized neural nets, and fuzzy-anatomic rules. The neural nets were trained with spiral CT data from 10 patients, not used in the following evaluation on spiral CT scans from 19 patients. An experienced radiologist verified the results. The true positive and false positive areas were compared in terms to the areas marked by the radiologist. The results were compared with a standard thresholding method. RESULTS The neural nets achieved a higher accuracy than the thresholding method. Cor…
A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images
2022
Abstract In precision agriculture, the accurate segmentation of crops and weeds in agronomic images has always been the center of attention. Many methods have been proposed but still the clean and sharp segmentation of crops and weeds is a challenging issue for the images with a high presence of weeds. This work proposes a segmentation method based on the combination of semantic segmentation and K-means algorithms for the segmentation of crops and weeds in color images. Agronomic images of two different databases were used for the segmentation algorithms. Using the thresholding technique, everything except plants was removed from the images. Afterward, semantic segmentation was applied usin…
A Modified Tabu Thresholding Approach for the Generalised Restricted Vertex Colouring Problem
1996
We present a modification of the Tabu Thresholding (TT) approach and apply it to the solution of the generalised restricted vertex colouring problem. Both the bounded and unbounded cases are treated. In our algorithms, the basic TT elements are supplemented with an evaluation function that depends on the best solution obtained so far, together with a mechanism which reinforces the aggressive search in the improving phase, and new diversification strategies which depend on the state of the search. The procedure is illustrated through the solution of the problem of minimising the number of workers in a heterogeneous workforce.
Filtering and emission area identification in the Time Resolved Imaging data
2012
Abstract Time Resolved Imaging (TRI) acquisitions allow precise timing analysis of emission spots. Up to date technologies deeply challenge their isolation by hiding the weak ones, under sizing or over sizing visually detectable emission spots and finally by jeopardizing timing resolution. We report on an algorithm based on 1 and 2D signal processing tools which automates the identification of emission sites and optimizes separation between noise and useful signal, even for weak spots surrounding strong emission areas. The application of the algorithm on several sets of data from different types of devices and their results are also discussed.
A Robust Multi Stage Technique for Image Binarization of Degraded Historical Documents
2017
International audience; Document image binarization is a central problem in many document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust multi stage framework that combines different existing document image thresholding methods for the purpose of getting a better binarization result. CLAHE technique is introduced to significantly enhance contrast in some poor images. The proposed method then uses a hybrid algorithm to partition image into foreground and background. A special procedure is finally applied in order to remove small noise and correct characters morphology. Experime…
Fuzzy temporal random sets with an application to cell biology
2007
Total Internal Reflection Fluorescence Microscopy (TIRFM) greatly facilitates to imaging the first steps of endocytosis, a process whereby cells traffic cargo from the cell surface to endosomes. Using TIRFM, fluorescent-tagged endocytic proteins are observed as overlapped areas forming random clumps of different sizes, shapes and durations. A common procedure to segment these objects consists of thresholding the original gray-level images to produce binary sequences in which a pixel is covered or not by a given fluorescent-tagged protein. This binary logic is not appropriate because it leaves a free tuning parameter to be set by the user which can influence on the conclusions of the statist…
Retinal vasculature segmentation and measurement framework for color fundus and SLO images
2020
Abstract The change in vascular geometry is an indicator of various health issues linked with vision and cardiovascular risk factors. Early detection and diagnosis of these changes can help patients to select an appropriate treatment option when the disease is in its primary phase. Automatic segmentation and quantification of these vessels would decrease the cost and eliminate inconsistency related to manual grading. However, automatic detection of the vessels is challenging in the presence of retinal pathologies and non-uniform illumination, two common occurrences in clinical settings. This paper presents a novel framework to address the issue of retinal blood vessel detection and width me…