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Thermal plasma spraying is an important manufacturing technique that creates a thermal barrier coating to protect the surface underneath from wear, erosion, oxidation and corrosion. In this paper, we develop a new microstructure classification and quantification (MCQ) module that could fully automatically classify and quantify two types of microstructures, globular and interlamellar, in the top coat...
We investigate efficient sensitivity analysis (SA) of algorithms that segment and classify image features in a large dataset of high-resolution images. Algorithm SA is the process of evaluating variations of methods and parameter values to quantify differences in the output. A SA can be very compute demanding because it requires re-processing the input dataset several times with different parameters...
Object detection and classification are two very important tasks for quality control in industrial process. The first step of a quality algorithm is the detection of the moving object. Afterwards, the detected object is classified according to its size and color related properties. In this study, an interactive image segmentation method is proposed to detect a moving object. The segmentation method...
In this research study, the authors developed the algorithms for computing the minimum distances between non-convex polygons. The purpose of the study is to develop the algorithm that transforms non-convex polygons into multi-convex polygons and the algorithm that computes the minimum distances between polygons on the basis of Gromov-Hausdorff and Gromov-Fréchet metrics. The proposed algorithms have...
The paper proposes a method for grouping fragments of contours of objects in the images of microscopic parasitological examinations, characterized by high transparency of analyzed objects. The method is based on a graphical representation of the edges in vector form, allowing to substantially reduce the required calculations. The method uses simple vector operations to determine stroke parameters...
We present a method of predictive reconstructing connections between parts of object outlines in images. The method was developed mainly to analyze microscopic medical images but is applicable to other types of images. Examined objects in such images are highly transparent, moreover close objects can overlap each other. Thus, segmentation and separation of such objects can be difficult. Another frequently...
Detection and segmentation of cells is an important step for classifying the cells as cancerous or non-cancerous. Pathologists use microscopic images for analysis and further diagnosis of cancer. These images contain the microscopic structure of tissues and are stained using some staining components to facilitate the process. Staining process varies due to different stain manufacturers, staining practices...
We develop a new object-based image analysis (OBIA) software system, named remote-sensing knowledge finder (RSFinder), based on the region-line primitive association framework (RLPAF). In this system, straight-edge lines are promoted as line primitives for OBIA, which is fundamentally different with common OBIA systems, such as eCogntion and ENVI feature extraction module. Based on region-line collaborative...
A synthetic image analysis method is proposed for in-situ detection of particle agglomeration for monitoring crystallization processes, based on using a non-invasive imaging system. The proposed method consists of image pre-processing, feature analysis, shape identification, and re-segmentation. Firstly, in-situ captured images are pre-processed to eliminate the influence from uneven illumination...
In order to reduce the effects caused by complex environments and ambient light conditions, a fast, robust and effective obstacles detection method of vehicles based on image analysis of multi-feature is proposed. Firstly, regions of interest (ROI) which contain lanes, vehicles and few parts of interference background are extracted in the input image by detecting gradient feature in rows. Secondly,...
With the recent developments in medicine and biology experiments a large amount of data is gathered in the form of multimedia elements (images, videos). Many algorithms have been developed and adapted based on the system of interest, and often the most challenging feature of the images may be used to facilitate a better analysis of the image. Herein, we developed an image analysis algorithm for quantification...
Recent advancement in genomics technologies has opened a new realm for early detection of diseases that shows potential to overcome the drawbacks of manual detection technologies. In this work, we have presented efficient contour aware segmentation approach based based on fully conventional network whereas for classification we have used extreme machine learning based on CNN features extracted from...
Recent advances in microcopy and improvements in image processing algorithms have allowed the development of computer-assisted analytical approaches in cell identification. Several applications could be mentioned in this field: cellular phenotype identification, disease detection and treatment, identifying virus entry in cells and virus classification; these applications could help to complement the...
Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from...
In the article the tasks of image processing and analysis in objects and processes control systems are described. The methods of image segmentation and image representation models are considered. The models of image representation designed by the authors are described. The presented models are based on image points energy estimation. To obtain the image points energy estimation (energy weights), the...
Atomic force microscopy is gaining interest as a technique to quantitatively study biological samples in native environment. However, the measuring principles behind may cause the presence of different sources of artifacts and image degradations. In this work, we present an AFM image analysis tool able to recognize morphological alterations in human leukemia cells after 3 h incubation with the antioxidant...
Mechanical forces play important roles in fetal lung development, therefore, pulmonary hypoplasia is an expected response to Oligohydramnios (OH) due to the decrease of fluid pressure. Amniotic sacs were punctured in pregnant mice with untouched fetuses serving as controls. Fetuses were delivered, and lung tissues collected. Histological sections were imaged and analyzed at the tissue level and the...
Immunohistochemical (IHC) markers viz., estrogen receptor (ER), progesterone receptor (PR) and proliferation marker Ki-67 are widely used for prognostic evaluation of breast cancer. The goal is to quantify the stained cells which are used to comment on the severity of cancer. In general, the expert pathologist performs the visual assessment task which is obviously tedious, time consuming and prone...
Several methods are exploited to watermark digital images as a safety measure for storing information, but an attacker can destroy the information by cropping a segment of the watermarked image. In recent years, numerous schemes were proposed that reduce the impact of such attacks. A new method has been proposed to confront cropping attack that is carried out using two sudoku tables. In this method,...
Tissue segmentation is an important pre-requisite for efficient and accurate diagnostics in digital pathology. However, it is well known that whole-slide scanners can fail in detecting all tissue regions, for example due to the tissue type, or due to weak staining because their tissue detection algorithms are not robust enough. In this paper, we introduce two different convolutional neural network...
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