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In recent years, the demands for LED are increasing. For testing the quality of LEDs, a lot of LED probes are necessary, so the high precision and efficient methods are paid more attention by industrial applications. This paper is focused on the measurement of the angle and the radius of a LED probe by computer vision. In previous paper, we proposed an effective method based on Canny edge detection...
This paper describes an efficient and accurate method using two 2-Dimensional bandpass filtered signals for edge detection of images, which are obtained by decomposing an image into two high frequency subband images in wavelet domain. Simulation results show that the proposed method has high accuracy in detecting the edge areas of image as is compared to existing methods. It provides new insights...
Image edge detection is sensitive to noise which is contained by natural images so that it affects the quality of the image segmentation. In order to remove noise and improve edge detection accuracy, then improving the quality of image segmentation, a novel image segmentation algorithm via neighborhood the principal component analysis and Laplace operator is proposed. The feature vectors of each pixel...
The solution in assisting practitioners in venipuncture is to design a full autonomous venous access device, which integrating multiple methods of venous detection in performing precision cannula placement [1]. Particularly, B-mode ultrasound and near-infrared imaging techniques are studied to conduct vessel reconstruction. However, low light level intensity and inherent speckle noise are problematic...
Graph-based signal processing (GSP) is an emerging field that is based on representing a dataset using a discrete signal indexed by a graph. Inspired by the recent success of GSP in image processing and signal filtering, in this paper, we demonstrate how GSP can be applied to non-intrusive appliance load monitoring (NALM) due to smoothness of appliance load signatures. NALM refers to disaggregating...
Synthetic Aperture Radar (SAR) is an active remote sensing technique. SAR is corrupted by a signal dependent multiplicative noise called speckle noise. Speckle noise limits the data extraction capabilities and degrades the quality of the obtained data. It decreases the potentiality to interpret the image, restricts edge abstraction, image segmentation, target recognition and classification. It is...
Moving objects often contain almost important information for surveillance videos, traffic monitoring, human motion capture etc. Background subtraction methods are widely exploited for moving object detection in videos in many applications. Moving object segmentation is the application in video processing. Segmentation helps in detecting various features of moving objects for further video/image processing...
Optical Coherence Tomography (OCT) is a noninvasive technique and depth-resolved imaging modality which is a prominent ophthalmic diagnostic tool. In this paper, an automated segmentation algorithm to detect few intra-retinal layers which are important for Edema detection present in Spectral Domain Optical Coherence Tomography (SDOCT) images is presented. An algorithm for accurate segmentation of...
We propose a novel depth maps refinement algorithm and generate multi-view video sequences from two-view video sequences for modern autostereoscopic display. In order to generate realistic contents for virtual views, high-quality depth maps are very critical to the view synthesis results. We propose an iterative depth refinement approach of a joint error detection and correction algorithm to refine...
In this paper, very simple automatic edge enhancement algorithm for Synthetic Aperture Radar (SAR) Image has been presented. Maximum Wavelet coefficients among three subbands at different scales have been exploited to form point wise maxima product. This operation produces enhanced edges in the wavelet domain itself. In many of the research works, development of edge enhancement step has been proposed...
This paper presents an automatic deblurring approach for motion blur images. The approach explores the prior of the intensity and gradient to estimate the motion blur kernel from single blurred image. In this way, motion blur kernel could be well estimated not only on daytime images, but also on nighttime images. Efficient optimization method was given for the prior-based approach. Besides, a cost-effective...
Paper currency recognition is an important concern for automation to improve our daily monetary activities. Such recognition system uses the banknote images to train a classifier for identification of unknown input notes. One of the basic problems of such system is high dimensional representation of the feature vector (more than 100 dimensions) of note images. Moreover, most of the traditional approaches...
This paper presents left ventricle (LV) endocardial segmentation from contrast 3D echocardiography (C3DE) images. The C3DE image segmentation is a very challenging problem. Though the image quality is perceived to be improved for visual analysis, the image quality actually deteriorates for the purpose of automatic/semi-automatic analysis due to high speckle noise. To overcome the speckle noise and...
In view of problem that it usually lacks of fusion depth to combine moment invariants with other extraction technology on local invariant features, this article proposes the moment invariants based on SUSAN initial edge response, which provides a sort of organic integration for moment invariants and SUSAN edge detection algorithm. The combination point is to treat SUSAN initial edge response matrix...
A conceptually simple hybrid Super Resolution (SR) algorithm is proposed using an adaptive edge sharpening algorithm. Most of the existing Super resolution algorithms are not robust to handle the high noisy conditions due to the ambiguity between the sharpening and denoising processes. The Low Resolution (LR) images are applied with the adaptive edge sharpening algorithm that is capable of capturing...
Edge detection is one of the prominent preprocessing stages in many image processing applications like Image Segmentation, Machine vision, Image Analysis and Feature Extraction etc. In order to get optimally true edge response in these applications, a particular edge detection technique shall be vulnerable to errors even when the input image gets contaminated due to presence of high frequency noise...
This paper presents a two stage process for image de-noising and edge enhancement by applying singular value decomposition technique on anisotropic diffused images. The two diffused versions of the input noisy image are generated in the first stage by anisotropic diffusion. The first diffused image is a well smoothed image and the second diffused image is sharp edge detected image. Singular value...
We present a novel iterative refinement process to apply to any stereo matching algorithm. The quality of its disparity map output is increased using four rigorously defined refinement modules, which can be iterated multiple times: a disparity cross check, bitwise fast voting, invalid disparity handling, and median filtering. We apply our refinement process to our recently developed aggregation window...
Medical Imaging has historically been very successful to expose the patient's anatomy beyond external visibility; thus, allowing more efficient and accurate treatments. The field of medicine continues to search for new techniques in order to increase accuracy, reduce complications, enable real-time feedback, allow early detection and reduce human errors. Various medical imaging techniques exist but...
Aiming at the problem that it is difficult to identify the fast moving objects in complex background, the paper proposes a method that establishes the inter-frame background sequence, and then multiply the pixel grayscale in the difference image. It defines constraint rules for public background image, gets moving target region with higher-order cumulant and block grayscale, and further highlights...
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