In case of robot vision, most important problem is the processing speed of acquiring and analyzing images are less than the speed of execution of the robot. In an actual robot color vision system, it is considered tha...
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In case of robot vision, most important problem is the processing speed of acquiring and analyzing images are less than the speed of execution of the robot. In an actual robot color vision system, it is considered that the system should be processed at real time. We guessed this problem might be solved using by the bicolor analysis technique. We have been testing a system which we hope will give us insight to the properties of bicolor vision. The experiment is used the red channel of a color CCD camera and an image from a monochromatic camera to duplicate McCann's theory. To mix the two signals together, the mono image is copied into each of the red, green and blue memory banks of the imageprocessing board and then added the red image to the red bank. On the contrary, pure color images, red, green and blue components are obtained from the original bicolor images in the novel color system after the scaling factor is added to each RGB image. Our search for a bicolor robot vision system was entirely successful.
Motion features extracted from video streams are used in a wide variety of computer visionapplications including action recognition. For this application many motion features are suggested in previous works and in or...
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ISBN:
(纸本)9781538644058
Motion features extracted from video streams are used in a wide variety of computer visionapplications including action recognition. For this application many motion features are suggested in previous works and in order to improve the results a group of them are used with some classification methods. In this paper, based on a bio-inspired motion perception model in animals, a new motion feature is proposed. The model is simple and could be realized with a limited number of mathematical operations and the process of feature extraction is much faster than well-known techniques such as histogram of optical flow (HOF) or motion boundary histogram (MBH). Moreover, with proposed modifications the feature becomes invariant to pixels' brightness and mostly sensitive to the magnitude of the motion. Empirical results on KTH dataset show that this new feature outperforms many other typical features in action recognition and competes HOF with acceptable result of (94.49%), while being much faster due to its low complexity.
There is clear need for integrated and affordable machinevision systems in line-scan applications, e.g. for width measurement and defect detection. These applications require sensor-like solutions in a price range no...
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ISBN:
(纸本)0819426377
There is clear need for integrated and affordable machinevision systems in line-scan applications, e.g. for width measurement and defect detection. These applications require sensor-like solutions in a price range not achievable with traditional machinevision systems consisting of a line-scan camera, host computer, frame grabber and possibly one or more dedicated processing boards. Since an integrated solution would make a separate host computer and associated boards unnecessary, we set out to study the feasibility of integrated machinevision technology for such applications. Analyses of several potential applications were used to define the requirements for an integrated line-scan camera-based vision system. In order to demonstrate the feasibility of the concept, a research prototype was designed based on these requirements. This is a complete machinevision system with camera front end, fast hardware for corrections, the necessary logic and a computer for higher-level data analysis and I/O. A 4096-pixel CCD array followed by 20 MHz 10 A/D conversion forms the front end. Illumination correction, geometric correction, 7x7 convolution, multilevel pixelwise thresholding and histogramming are all implemented with fast Erasable Programmable Logic Device (EPLD) circuits. A compact PC/104 with a 486 processor takes care of the high-level processing and control. Communication facilities include 12 TTL-level I/O lines, a serial line and a video output.
Traditional image signal processors (ISPs) are primarily designed and optimized to improve the image quality perceived by humans. However, optimal perceptual image quality does not always translate into optimal perfor...
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ISBN:
(纸本)9781538662496
Traditional image signal processors (ISPs) are primarily designed and optimized to improve the image quality perceived by humans. However, optimal perceptual image quality does not always translate into optimal performance for computer visionapplications. We propose a set of methods, which we collectively call visionISP, to repurpose the ISP for machine consumption. visionISP significantly reduces data transmission needs by reducing the bit-depth and resolution while preserving the relevant information. The blocks in visionISP are simple, content-aware, and trainable. Experimental results show that visionISP boosts the performance of a subsequent computer vision system trained to detect objects in an autonomous driving setting. The results demonstrate the potential and the practicality of visionISP for computer visionapplications.
In nuclear power plants, visual testing (VT) based on video images taken from an underwater camera is carried out. However, it is a problem in that a lot of noise is superimposed on VT images due to radiation exposure...
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ISBN:
(纸本)9784901122160
In nuclear power plants, visual testing (VT) based on video images taken from an underwater camera is carried out. However, it is a problem in that a lot of noise is superimposed on VT images due to radiation exposure. We propose a technique for improving the quality of those images by imageprocessing that includes radiation noise reduction and signal enhancement. Real-time video processing was realized by applying the proposed technique with a parallel processing unit. Improving the clarity of VT images will lead to a reduced burden placed on inspectors.
Color representation and comparison based on the histogram has proved to be very efficient for image indexing in content-based image retrieval and machinevisionapplications. However, the issues of color constancy an...
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ISBN:
(纸本)0819437611
Color representation and comparison based on the histogram has proved to be very efficient for image indexing in content-based image retrieval and machinevisionapplications. However, the issues of color constancy and accurate color similarity measures remain unsolved. This paper presents a new algorithm for intensity-insensitive color characterization for image retrieval and machinevisionapplications. The color characterization algorithm divides the HSI (hue, saturation and intensity) color space into a given number of bins in such a way that the color characterization represents all the colors in the hue/saturation plane as well as black, white and gray colors. The color distribution in these bins of the HSI space is represented in the form of a one-dimensional vector called Color Spectrum Vector (CSV). The color information that is stored in the CSV is insensitive to changes in the luminance. A weighted version of CSV called WCSV is introduced to take the similarity of the neighboring bins into account A Fuzzy Color Spectrum Vector (FCSV) color representation vector that takes into account the human uncertainty in color classification process is also introduced here. The accuracy and speed of the algorithm is demonstrated in this paper through a series of experiments on image indexing and machinevisionapplications.
the human vision system is always looking for important and valuable areas to get the most information from the visual data in the shortest possible time. For this purpose, visual attention guides the vision system to...
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ISBN:
(纸本)9781538644058
the human vision system is always looking for important and valuable areas to get the most information from the visual data in the shortest possible time. For this purpose, visual attention guides the vision system to the salient regions. Unfortunately, some of the salient regions, in terms of the human vision system, have a high potential for attracting attention, but do not contain important and useful information. Therefore, attention and concentration on these salient regions will cause the loss of time and distraction of the audience's senses from the main subject of the image. Therefore, detecting and eliminating these regions, which are called distractors, can be of great help in order to increase the quality of the image, increase the accuracy of the algorithms based on saliency detection and not losing a lot of time in real-time applications. In this paper, pixel-based features are extracted from different approaches for training and test images and after segmentation the images, segment-based features are generated. After determining the class of each segment of the training images according to the corresponding masks, the test image segments are classified according to the TPTSSR method based on sparse coding and representation system in terms of the severity of the distractor in the 9 different classes. To evaluate MSE metric leads to unreliable results in conditions of class unbalancing, a new metric will be introduced to evaluate the results. The implemented results show that the proposed method has a higher accuracy than the previous ones in terms of these two metrics.
image segmentation is an important and difficult issue in computer vision and imageprocessing. It is categorized into two categories, supervised image segmentation and unsupervised image segmentation. The supervised ...
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ISBN:
(纸本)9784901122160
image segmentation is an important and difficult issue in computer vision and imageprocessing. It is categorized into two categories, supervised image segmentation and unsupervised image segmentation. The supervised method are not convenient since it needs the interactions of users. In this paper, we proposed an unsupervised method. It uses a defocus map, edge and color as similarity attributes of pixels or superpixels to generate an edge strength map. Then, we construct a minimum spanning tree with the superpixels and the edge map to divide the image to the foreground and background. In our experiment, our method doesn't need user interaction and the performance is better than previous superpixels grouping methods.
Due to our aging society, driver assistance and automated driving have been intensely researched. Recognizing the surrounding environment utilizing imageprocessing is a core technological element for driving intellig...
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ISBN:
(纸本)9784901122160
Due to our aging society, driver assistance and automated driving have been intensely researched. Recognizing the surrounding environment utilizing imageprocessing is a core technological element for driving intelligence. Specifically, technology must accurately detect pedestrians, obstacles such as other vehicles, condition of a driver, weather, etc. using cameras and various sensors. In this presentation, I introduce image recognition technology necessary for driver assistance.
We will present a cost-effective and flexible realization of High Performance Computing (HPC) clustering and its potential in solving computationally intensive problems in computer vision. The featured software founda...
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ISBN:
(纸本)9780769533322
We will present a cost-effective and flexible realization of High Performance Computing (HPC) clustering and its potential in solving computationally intensive problems in computer vision. The featured software foundation to support the parallel programming is the GNU Parallel Knoppix package with Message Passing Interface (MPI) based Octave, Python and C interface capabilities. The implementation is especially of interest in applications where the main objective is to reuse the existing hardware infrastructure and to maintain the overall budget cost. We will present the benchmark results and compare and contrast the performances of Octave and MATLAB.
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