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In recent years, with the explosion of digital images on the Web, content-based retrieval has emerged as a significant research area. Shapes, textures, edges and segments may play a key role in describing the content of an image. Radon and Gabor transforms are both powerful techniques that have been widely studied to extract shape-texture-based information. The combined Radon-Gabor features may be...
Determining the centroids of circular marks is a problem that arises in many applications, for example, fluid mechanics, computer graphics, coordinate meteorology, statistics, etc. The accuracy of determining the centroids of circular marks in images is important for the overall accuracy of measurements. Therefore, the aim of the present work is to determine the centroids of these circular marks with...
A new algorithm is introduced to compute the curve skeleton of 3D objects by using the notion of local convexity. The centers of maximal balls detected on the distance transform of the object are filtered to select as anchor points only those located on sharp local convexities of the object's boundary. Then, the skeleton is obtained by means of topology preserving removal operations. Pruning is finally...
This paper considers using deep neural networks for handwritten Chinese character recognition (HCCR) with arbitrary position, scale, and orientations. To solve this problem, we combine the recently proposed spatial transformer network (STN) with the deep residual network (DRN). The STN acts like a character shape normalization procedure. Different from the traditional heuristic shape normalization...
This paper investigates the application of flexible and effective fast-convolution (FC) filtering scheme for multiplexing OFDM physical resource blocks (PRBs) in a spectrally well-localized manner. The scheme is able to suppress interference leakage between adjacent PRBs, thus supporting independent waveform parametrization for different PRBs, as well as asynchronous multiuser operation. These are...
Thanks to the rise of wearable and connected devices, sensor-generated time series comprise a large and growing fraction of the world's data. Unfortunately, extracting value from this data can be challenging, since sensors report low-level signals (e.g., acceleration), not the high-level events that are typically of interest (e.g., gestures). We introduce a technique to bridge this gap by automatically...
The census transform in computing the matching cost of stereo matching is simple and robust under luminance variations in stereo image pairs; however, different disparity maps are generated depending on the shape and size of the census transform window. In this paper, we propose a stereo matching method with variable sizes of census transform windows based on the gradients of stereo images. Our experiment...
Many algorithms in computer vision, e.g., for object localization, are supervised and need annotated training data. One approach for object localization is the Discriminative Generalized Hough Transform (DGHT). It achieves state-of-the-art performance in applications like iris and epiphysis localization, if the amount and quality of training data is sufficient. This motivates techniques for extending...
Precise segmentation of Pap smear cell nucleus is crucial for early diagnosis of cervical cancer. This task is particularly challenging because of cell overlapping, inconsistent staining, poor contrast and other imaging artifacts. In this study, a novel method is proposed to segment cell nucleus from overlapping Pap smear cell images. The proposed technique introduces a circular shape function (CSF)...
Lung cancer is the foremost cause of death in many regions of the world. Early detection betters the chances of survival. PA chest radiography is the most commonly used diagnosis tool for detecting lung tumor, because it is cost effective and requires less radiation dose. Radiologists fail to detect nodule from PA chest radio graphs, at early stage because of complex anatomical structure present in...
Fast power line detection in images is useful in photogrammetry applications such as measuring wire tension and sag. To make these measurements, images of entire power line spans must be used which may include large amounts of curvature. Previous work in power line detection has focused on aerial or close proximity images where no power line curvature is visible. This paper assesses feasibility of...
This paper proposes the novel method which detect circles in an image by an approach of the template matching, not an approach of the Circle Hough Transform(CHT) voting edge points to the parameter space. The approach such as the Hough transform needs huge computing cost and huge memory. Furthermore, a lot of false circles are detected in a complicated background. In order to overcome these problems,...
Segmentation of cell nuclei is an important step towards automatic analysis of microscopic images. This paper presents an automated technique for nuclear segmentation in skin histopathological images. The proposed technique first detects nuclear seeds using a bank of generalized Laplacian of Gaussian (gLoG) kernels. Based on the detected nuclear seeds, a multi-scale radial line scanning (mRLS) method...
In order to efficiently recognize actions from depth sequences, we propose a novel feature, called Global Ternary Image (GTI), which implicitly encodes both motion regions and motion directions between consecutive depth frames via recording the changes of depth pixels. In this study, each pixel in GTI indicates one of the three possible states, namely positive, negative and neutral, which represents...
The fast temporal-dynamics and intrinsic motion segmentation of event-based cameras are beneficial for robotic tasks that require low-latency visual tracking and control, for example a robot catching a ball. When the event-driven iCub humanoid robot grasps an object its head and torso move, inducing camera motion, and tracked objects become no longer trivially segmented amongst the mass of background...
The class of objects that can be represented by surfacesof revolution (SoRs) is highly prevalent in human work andliving spaces. Due to their prevalence and convenient geometricproperties, SoRs have been employed over the pastthirty years for single-view camera calibration and pose estimation,and have been studied in terms of SoR object reconstructionand recognition.Such treatment has provided techniques...
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...
The Gamma-Gamma (G-G) distribution which is one of the most important distributions has been introduced to model the irradiance. One famous study has relied on a method of moment technique involving fractional moments to estimate the parameters of the G-G distribution. The mean square error of these parameter estimates is large in cases where the Rytov variance is small or the true distribution of...
The max-tree is a mathematical morphology data structure that represents an image through the hierarchical relationship of connected components resulting from different thresholds. It was proposed in 1998 by Salembier et al., since then,many efficient algorithms to build and process it were proposed.There are also efficient algorithms to extract size, shape and contrast attributes of the max-tree...
This paper proposes an eye state detection system using Haar Cascade Classifier and Circular Hough Transform. Our proposed system first detects the face and then the eyes using Haar Cascade Classifiers, which differentiate between opened and closed eyes. Circular Hough Transform (CHT) is used to detect the circular shape of the eye and make sure that the eye is detected correctly by the classifiers...
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