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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...
Circles detection is an important part of object recognition in image processing and computer vision. In this paper, we propose an adaptive method based on Hough transform to detect the circle shapes in digital image. The Mexican Hat filter derived from edge filter is used to concentrate the peaks of Hough local maxima. So, the circle center and its radius can be extracted easily and accurate. The...
In shape learning for a digital image, it is a common that one would encountered two major problems, which are noise and missing edges. The existing research approaches aim to reduce noise, while at the same time to recover the missing edges. However, noise reductions using contour detector or smoothening techniques could indirectly distort the salient boundary. Most of the research works only focus...
Autonomous Underwater Vehicle docking technology is now extensively used in the field of underwater. Vision guidance, as one of its core components, shows a great development prospect. In this paper, a brief description of the vision guidance models and the previous algorithm were described. Both the advantages and disadvantages of that algorithm would be analyzed. By using grey-scale feature analysis,...
The proposed algorithm is designed to detect the boundary of a region which can be identified by some characteristic feature at a general level, but heterogeneity within the region itself prevents the use of standard gradient techniques. The general principle of the algorithm is based on inner boundary tracing and involves three techniques- Technique of Tracing, Technique for Convex Turns and Technique...
Ant Colony Optimization (ACO) is a nature inspired algorithm for solving optimization problems and is proved to be a powerful tool in image processing. It works on the principle that an ant while moving leaves pheromones on its path, which is used as guide to be followed by other ants. ACO is complex and time consuming. In this paper, a multi-threading based implementation of ACO is proposed for identifying...
In this paper, a small set of features based on local appearance and texture is applied to the task of image recognition and classification. These features are used to train and subsequently test three different machine learning techniques, namely k-Nearest Neighbors (K-NN), Support Vector Machines (SVM) and Ensemble Learning (Bagging). A case study on a publicly available object classification dataset...
The ability to detect and localize an object of interest from a captured image containing a cluttered background is an essential function for an autonomous robot operating in an unconstrained environment. In this paper, we present a novel approach to refining the pose estimate of an object and directly labelling its contours by dense local feature matching. We perform this task using a new image descriptor...
Prostate diseases are very common in adult and elderly men, and prostate boundary detection from images plays a key role in prostate disease diagnosis and treatment. The edges in an image usually refer to rapid changes in some physical properties, such as geometry, illumination. There are many ways to perform the edge detection. However, it may be grouped into two categories, that are gradient and...
Edge detection plays an important role in flame and fire image processing. Analysis and monitoring of flame images has been done continuously to measure the visible area of a flame for providing the additional information such as fire region, effect, gases etc. An accurate value of an area could be obtained only if continuous and smooth boundary of flame shall be detected. Several traditional edge...
Lung cancer is one of the malignant tumors with the fastest increasing speed of incidence and death rate. It appears in the form of spherical nodules in a conventional radiograph. However, some lung nodules are not be able to be detected due to their overlap with normal anatomic structures such as ribs and clavicles. In this paper, a rib suppression method based on principle component analysis (PCA)...
Edge detection remains a challenging task in many applications even with the abundance of commonly used methods such as Sobel, Robert, Prewitt, Canny, and Cellular Automata. In this paper, a new method is proposed for edge detection using morphological operations and utilizing erosion processes to identify the edges in an image. In this work we propose to use morphological operators of disk shape...
In this work a new method for image edge detection based on multilayer perceptron (MLP) is proposed. The method is based on updating a MLP to learn a set of contours drawn on a 3×3 grid and then take advantage of the network generalization capacity to detect different edge details even for very noisy images. The method is applied first to Gray scale images and can be easily extended to color ones...
This paper proposes a novel method for the detection and segmentation of pectoral muscle in mammograms using fractal-based analysis. The region of pectoral muscles containing the brightest pixels has an adverse effect, during the detection of microcalcifications in a mammogram and hence detection and segmentation of pectoral muscle is deemed as an important preprocessing step. This proposed technique...
A mammography exam, called a mammogram, is an important examination aid that is designed to help human in the early detection and diagnosis of breast diseases especially in women. Image processing is using for detecting for objects in mammogram images. Edge detection; which is a method of determining the discontinuities in gray level images; is a very important initial step in Image processing. Many...
Image segmentation is a very important step in order to accomplish automatic tasks, such as classification, being continuously demanded by our society. However, the particular case of naval images entails issues that may exacerbate the conditions for segmentation. Specifically due to water reflections the gray distribution might be very disperse throughout the image and waves produce a large amount...
The shape of a burner flame is an important characteristic closely linked to the burner configuration, fuel type, and other operational parameters of a combustion process. This paper presents an algorithm to extract the 3-D medial axis of a burner flame and use it as a descriptor for the flame shape characterization. The algorithm is based on the 2-D medial axes of two flame images captured from two...
A method to determine whether a pixel is the edge point of a color image is presented. First, according to the characteristic of RGB color space, a color triangle of a pixel is constructed with its color coordinates RGB, and then the perimeter and the internal angle of the color triangle which can be seen as the information value of a pixel is calculated. Last, comparing the value with that in its...
Edge detection is one of the most challenging tasks in image processing. A scheme for edge detection of images based on multi-scale morphology is presented in this paper. Mathematical morphology is a mathematic tool to analyze the image based on the structuring element. The morphological edge detection operator is non-linear difference operator. The results due to the proposed method have been found...
Edge detection is widely applied in digital image processing, especially in segmentation of images. Many of the well-known edge detectors, e.g., Sobel and Canny operator, are based on spatial filtering with a mask around the pixel under detection. In this paper, we propose a very low complexity edge detector that has two operation modes; non-causal mode and causal mode. Though simple in its form,...
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