Three-dimensional data present pertinent information about geometrical features of an object. It has been a classical approach that image data acquired by range sensors are processed as traditional 2.5-dimensional (2....
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ISBN:
(纸本)0819429821
Three-dimensional data present pertinent information about geometrical features of an object. It has been a classical approach that image data acquired by range sensors are processed as traditional 2.5-dimensional (2.5-D) images. Range data have rich information that needs some special treatment in order to fully understand and utilize them. In this report, two case studies are presented to investigate the 3-D aspects of range data and applied them to solve practical problems in manufacturing environment. The first case is the classical 'pick and place' problem where the range data were taken on the holding rack of car doors and there is a need to identify multiple holding points accurately, with the rack almost taking entire field of view and traditional imageprocessing approach invalid. The second case is the range data correction and sub-pixel patch with large field of view. The applications are in automated quality assessment. Two approaches are from different vision solutions with one objective that is to process range image data with 3-D representation instead of that of traditional 2.5-D.
Multi-focus image fusion is a process that fuses several images from a scene with different focal lengths into a whole image in which all areas are focused on. image fusion methods in the Discrete Cosine Transform (DC...
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ISBN:
(纸本)9781538644058
Multi-focus image fusion is a process that fuses several images from a scene with different focal lengths into a whole image in which all areas are focused on. image fusion methods in the Discrete Cosine Transform (DCT) domain are efficient due to their low time and energy consumption, and low complexity. This is especially true when fusing images are compressed in JPEG format in visual Sensor Networks (VSN). In this paper, a low complexity multi-focus image fusion in DCT domain is presented which increases the output image quality. Our proposed method makes it suitable for real-time applications because of its implementation in DCT domain. On the other hand, it is stable in noisy conditions. The proposed method uses the singular values of Singular Value Decomposition (SVD) of 8x8 input blocks in DCT domain. The geometric mean of the 5 largest singular values (out of 8 singular values) is computed as a criterion of focused block detection. The blocks which have the highest geometric mean value among other corresponding blocks is selected as the focused block. These blocks are then used for constructing the output image. This method can be utilized both in DCT domain and in spatial domain. Various experiments and comparisons between the proposed method and the previous methods in noisy and noiseless conditions have been presented, which confirm the increase in image quality and stability in noisy images.
This paper will argue in favor of a comprehensive model of image data bases, which allows the inclusion of computer vision technique into a formal query framework built on a rigorous data base foundation. It attempts ...
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ISBN:
(纸本)0819456438
This paper will argue in favor of a comprehensive model of image data bases, which allows the inclusion of computer vision technique into a formal query framework built on a rigorous data base foundation. It attempts to give a first, very tentative direction that this framework could take. The main idea of the paper is that a correct way to create a data base that relies on such heterogeneous techniques as those developed by computer vision researchers without collapsing under the sheer weight of its own complexity goes through the definition of abstract data types, and of suitable techniques to manipulate them in a query system without having to know anything of their implementation, that is, purely from a functional point of view.
In order to enhance the speed of imageprocessing we apply the optical wavelet transform to vision system by the method of photoelectric hybrid implementation. The state-of-the-art liquid crystal on silicon (LCoS) tec...
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ISBN:
(纸本)0819451541
In order to enhance the speed of imageprocessing we apply the optical wavelet transform to vision system by the method of photoelectric hybrid implementation. The state-of-the-art liquid crystal on silicon (LCoS) technology is applied to improve the signal-to-noise ratio of the wavelet transform. A fan out grating implemented by a phase-only LCoS is used to implement multiple channel optical processing. Therefore the parallelism of the vision system is improved further. The research results shows that the optical wavelet transform based vision system is reasonable and feasible. The image feature extraction by optical information processing can enhance the speed of visionprocessing.
Deep learning-based approaches, such as Convolutional Neural Nets (CNNs), have shown high performance in classifying contents of images. CNNs, however, have the notable drawbacks of potentially high computing costs, p...
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ISBN:
(纸本)9781510674219;9781510674202
Deep learning-based approaches, such as Convolutional Neural Nets (CNNs), have shown high performance in classifying contents of images. CNNs, however, have the notable drawbacks of potentially high computing costs, poor explainability, and wide performance variance if the underlying imagery data deviates from the training baseline. As advanced imageprocessing capabilities are matured, the on-board detection of objects in space-based imagery is increasingly proposed. On-board satellite processingapplications, which may be resource-limited, can drive the need for simpler models that reduce the necessary computing burden for edge computing applications. This raises the question of how well classic computer vision techniques can compete with more modern approaches. This paper characterizes and compares the performance of multiple computer vision models for the application of distinguishing maritime vessels from typical clutter in commercial electrooptical (EO) satellite imagery. A Support Vector machine (SVM) model using manually curated features is compared to multiple DL-based models spanning a range of model sizes, with the goal of determining whether classical approaches can compete favorably with DL when computational resources are taken into consideration. Differences in performance and processing resources are characterized between the approaches. Findings include that the SVM-based model may approach the accuracy of some CNN-based models for classifying images of clouds in satellite EO imagery for smaller DL-based models. However, even the smallest DL-based models, which take about the same computational resources as the SVM-based model, generally out-perform the SVMbased model. This finding may have implications for the operational use of on-board processing techniques for satellite payloads.
We present a sensor fusion framework for real-time tracking applications combining inertial sensors with a camera. In order to make clear how to exploit the information in the inertial sensor, two different fusion mod...
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ISBN:
(纸本)9780819490254
We present a sensor fusion framework for real-time tracking applications combining inertial sensors with a camera. In order to make clear how to exploit the information in the inertial sensor, two different fusion models gyroscopes only model and accelerometers model are presented under extended Kalman filter framework. Gyroscopes only model uses gyroscopes to support the vision-based tracking without considering acceleration measurements. Accelerometers model utilizes both measurements from the gyroscopes, accelerometers and vision data to estimate the camera pose, velocity, acceleration and sensor biases. Synthetic data and real image experimental sequences show dramatic improvements in tracking stability and robustness of estimated motion parameters for gyroscope model, when the accelerometer measurements exist drift.
PCI bus mastering with a frame grabber provides a 40 times speed improvement over ISA bus frame grabbing while lowering frame grabber costs by more than 50%.
ISBN:
(纸本)0819419613
PCI bus mastering with a frame grabber provides a 40 times speed improvement over ISA bus frame grabbing while lowering frame grabber costs by more than 50%.
This paper addresses the problem of face recognition using a graphical representation to identify structure that is common to pairs of images. Matching graphs are constructed where nodes correspond to image locations ...
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ISBN:
(纸本)9780819499417
This paper addresses the problem of face recognition using a graphical representation to identify structure that is common to pairs of images. Matching graphs are constructed where nodes correspond to image locations and edges are dependent on the relative orientation of the nodes. Similarity is determined from the size of maximal matching cliques in pattern pairs. The method uses a single reference face image to obtain recognition without a training stage. The Yale Face Database A is used to compare performance with earlier work on faces containing variations in expression, illumination, occlusion and pose and for the first time obtains a 100% correct recognition result.
The benefits of layering in software applications are well-known not only to authors and industry experts, but to software enthusiasts as well because the layering provides a testable and more error-proof framing for ...
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ISBN:
(纸本)9789897585111
The benefits of layering in software applications are well-known not only to authors and industry experts, but to software enthusiasts as well because the layering provides a testable and more error-proof framing for applications. Despite the benefits, however, the increasingly popular area of machine learning is yet to embrace the advantages of such a design. In the present paper, we aim to investigate if characteristic benefits of layered architecture can be applied to machine learning by designing and building a system that uses a layered machine learning approach. Then, the implemented system is compared to other already existing implementations in the literature targeting the field of facial recognition. Although we chose this field as our example for its literature being rich in both theoretical foundations and practical implementations, the principles and practices outlined by the present work are also applicable in a more general sense.
We describe the motivations behind a generic imageprocessing and computer vision platform that emphasises the integration of rapid algorithm development within a graphical front end and turn-key end use. A new modula...
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