In this paper is addressed the development of an ultrasonic sensor for the material identification. This sensor had to be appropriate, in terms of computational cost, in order to be implemented in small robots. This i...
详细信息
ISBN:
(纸本)9781467307536
In this paper is addressed the development of an ultrasonic sensor for the material identification. This sensor had to be appropriate, in terms of computational cost, in order to be implemented in small robots. This implementation was achieved by a novel signalprocessing method called Peniel. The associated electronic circuit and the algorithm of this method have as main strengths their circuital simplicity and the low computational cost, respectively. These two characteristics let the sensor to be implemented in two robots of the low cost robotic kit TEAC(2)H-RI, which was constructed as part of the master thesis of one the authors. The developed system was proved with acrylic, aluminium and glass samples. In the performed experiments those materials were identified with 100% accuracy in all of ten trials. According to the literature review, it is the first time which is achieved the implementation of the ultrasonic material identification in a robotic system.
We propose a new texture segmentation algorithm to improve the segmentation of boundary areas in the image. In some applications such as medical image segmentation, an exact segmentation on the boundary areas is neede...
详细信息
ISBN:
(纸本)9781424407071
We propose a new texture segmentation algorithm to improve the segmentation of boundary areas in the image. In some applications such as medical image segmentation, an exact segmentation on the boundary areas is needed. But satisfactory segmentation results cannot be obtained on the boundary areas among different texture classes with some existing texture segmentation algorithms in our preliminary experiments. The proposed algorithm consists of three steps. The first step is to apply the K-View-datagram segmentation method to the image to obtain an initial segmentation;the second step is to find a boundary set which includes the pixels with high probabilities to be misclassified by the initial K-View-datagram segmentation;the third step is to apply a modified K-views template method with a small scanning window to the boundary set to refine the segmentation. The evaluation of the proposed algorithm was carried out with the benchmark images randomly taken from Brodatz Gallery and the ultrasonic prostate images provided by the hospitals. Initial experimental results show that the concept of boundary set defined in this paper can catch most of misclassified pixels of the output of the initial K-View-datagram segmentation. The new segmentation algorithm gives high segmentation accuracy and classifies the boundary areas better than the existing algorithms.
Line follower robots can be used for many important robotic and industrial tasks. One of the most important factors in these methods is the computational requirement of the algorithm. The paper presents a novel method...
详细信息
ISBN:
(纸本)9781538646403
Line follower robots can be used for many important robotic and industrial tasks. One of the most important factors in these methods is the computational requirement of the algorithm. The paper presents a novel method for the line following problem using imageprocessing technique. Our main goal is to find an efficient way with real-time computing to track a line using a camera-equipped robot. To measure the effectiveness of the presented method, we compare two line following robots with the line tracking method being the only difference between them. The first robot uses the proposed camera-based method and the other robot has reflective optical sensors in order to determine the position of the line. These real life experiments demonstrate the efficiency of the presented method.
The main objective of this paper by using imageprocessing algorithms, mainly Hough algorithm, to develop a system which is able to analyze, process and put in evidence all the necessary features of a CT image for dia...
详细信息
ISBN:
(纸本)9781728195438
The main objective of this paper by using imageprocessing algorithms, mainly Hough algorithm, to develop a system which is able to analyze, process and put in evidence all the necessary features of a CT image for diagnosing pulmonary fibrosis. To approach the presented topic, imageprocessing algorithms, image filtering, together with the Matlab work environment were combined and the optimal solution was finally implemented. The main idea behind the method is to identify two types of lines of the CT image which gives to the specialist the correct diagnostic by interpreting the obtained results. As final results, the chosen solution incorporates some crucial steps which have to be done in order to obtain the desired processed image with all the important details visible. The final solution was tested on different CT images and the medical specialist used it for detecting this type of disease, the detection being very easily mistaken.
Twenty-five years ago, the field of computational imaging arguably did not exist, at least not as a standalone arena of research activity and technical development. Of course, the idea of using computation to form ima...
详细信息
Twenty-five years ago, the field of computational imaging arguably did not exist, at least not as a standalone arena of research activity and technical development. Of course, the idea of using computation to form images had been around for several decades, largely thanks to the development of medical imaging-such as magnetic resonance imaging (MRI) and X-ray tomography-in the 1970s and synthetic-aperture radar (SAR) even earlier. Yet, a quarter of a century ago, such technologies would have been considered to be a subfocus of the wider field of imageprocessing. This view started to change, however, in the late 1990s with a series of innovations that established computational imaging as a scientific and technical pursuit in its own right.
In this paper, an enhanced sparse representation approach is proposed to estimate the 3D shapes of objects in 2D image sequences. In the proposed method, the unknown 3D shape is estimated via a two-stage scheme, namel...
详细信息
In this paper, an enhanced sparse representation approach is proposed to estimate the 3D shapes of objects in 2D image sequences. In the proposed method, the unknown 3D shape is estimated via a two-stage scheme, namely the main 3D shape estimation stage and the compensatory 3D shape estimation stage. Moreover, a reweighted sparse representation model is constructed to extract the shape bases for each estimation stage. In the sparse model, a reweighted constraint is enforced to enhance the coefficient sparsity of the shape bases. Experimental results on the well-known CMU image sequences demonstrate the effectiveness and feasibility of the proposed approach.
This paper presents a fast image restoration method using the 2-D block Kalman filter with colored driving source. The remarkable feature of the proposed method is reduced computational complexity using the high corre...
详细信息
ISBN:
(纸本)9781479947966
This paper presents a fast image restoration method using the 2-D block Kalman filter with colored driving source. The remarkable feature of the proposed method is reduced computational complexity using the high correlation pixels of current region and reference region, while the conventional 2-D block Kalman filter methods performed image restoration without considering the relationship between the reference region and the current region. We have shown the effectiveness of the proposed method by numerical results and subjective evaluation results.
作者：
Yang NiWang Yu-tianYanshan Univ
Measurement Technol & Instrumentat Key Lab Hebei He Bei Qin Huangdao 066004 Peoples R China
Non-touch on-line thickness measurement using CCD vision system is present. Measurement principle, composition of the detection system and the operation process are expatiated. Mathematical morphology theory is succes...
详细信息
ISBN:
(纸本)9780769533117
Non-touch on-line thickness measurement using CCD vision system is present. Measurement principle, composition of the detection system and the operation process are expatiated. Mathematical morphology theory is successfully used in thickness image analysis and imageprocessing. Distance of two light beams represents the measured thickness. Center orientation is a key aspect of improving precision of thickness measurement. Morphology thinning algorithm is proposed to locate the central lines of line-structured light image. The algorithm can safely thin entities to their central points. Experimental results show that the measurement error is less than 0.8%, and the morphological algorithm presented here is adaptable to real time imageprocessing.
image reconstruction techniques from signals received by sensors find application in several fields, including radio interferometry for astronomical investigations and magnetic resonance imaging for medical applicatio...
详细信息
ISBN:
(纸本)9781509004805
image reconstruction techniques from signals received by sensors find application in several fields, including radio interferometry for astronomical investigations and magnetic resonance imaging for medical applications. This paper presents a novel method for image reconstruction based on the iterative scanning of a region of interest. A modified approximate message passing (AMP) algorithm is adopted to extract relevant image information with low computational complexity from signals received by sensors. The method is illustrated by simulations, with reference to the LOFAR radio interferometer, and compared in the case of radio astronomy with the CLEAN algorithm.
The Szechenyi Istvan University race car team is an active and successful participant of the Shell Eco-marathon for long time ago. The Shell introduces the autonomous vehicle category on the Eco-marathon for 2018. Our...
详细信息
ISBN:
(纸本)9781538646403
The Szechenyi Istvan University race car team is an active and successful participant of the Shell Eco-marathon for long time ago. The Shell introduces the autonomous vehicle category on the Eco-marathon for 2018. Our long-term goal is to make the Szenergy racing team's vehicle suitable for the autonomous category. The first milestone is to make a reliable computer vision based intelligent detection system that understands the environment of the racing car. In this paper we will present a solution for racetrack detection i.e. a fusion of imageprocessing and neural network systems. The two-stage recognition system is at the first phase an imageprocessing algorithm which finds the red-white and blue-white striped edge of the road, and at the second phase, a pre-trained superpixel-based neural network which recognize the road on the filtered image.
暂无评论