The registration of images is a fundamental task in numerous applications in medical imageprocessing. Similarity measure is an important key in intensity based image registration. Here, we propose correntropy measure...
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ISBN:
(纸本)9781467361842
The registration of images is a fundamental task in numerous applications in medical imageprocessing. Similarity measure is an important key in intensity based image registration. Here, we propose correntropy measure as similarity measure in mono modal setting. Correntropy is a important measure between two random variables based on information theoretic learning and kernel methods. This measure is useful in nonGaussian signal processing. In this paper, this measure is used in image registration. Here, we analytically illustrate that this measure is robust in presence of spiky noise (impulsive noise). The experimental results show that the proposed similarity has better performance than traditional intensity-based similarity measures such as Mutual information and SSD.
The highest barriers to wide scale implementation of vision systems have been cost. This is closely followed by the level of difficulty of putting a complete imaging system together. As anyone who has ever been in the...
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ISBN:
(纸本)0819426377
The highest barriers to wide scale implementation of vision systems have been cost. This is closely followed by the level of difficulty of putting a complete imaging system together. As anyone who has ever been in the position of creating a vision system knows, the various bits and pieces supplied by the many vendors are not under any type of standardization control. In short, unless you are an expert in imaging, electrical interfacing, computers, digital signal processing, and high speed storage techniques, you will likely-spend more money trying to do it yourself rather than to buy the exceedingly expensive systems available. Another alternative is making headway into the imaging market however. The growing investment in highly integrated CMOS based imagers is addressing both the cost and the system integration difficulties. This paper will discuss the benefits gained from CMOS based imaging, and how these benefits are already being applied.
This work classifies color images of ships attained using cameras mounted on ships and in harbors. Our data-sets contain 9 different types of ship with 18 different perspectives for our training set, development set a...
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ISBN:
(纸本)9780819494344
This work classifies color images of ships attained using cameras mounted on ships and in harbors. Our data-sets contain 9 different types of ship with 18 different perspectives for our training set, development set and testing set. The training data-set contains modeled synthetic images;development and testing data-sets contain real images. The database of real images was gathered from the internet, and 3D models for synthetic images were imported from Google 3D Warehouse. A key goal in this work is to use synthetic images to increase overall classification accuracy. We present a novel approach for autonomous segmentation and feature extraction for this problem. Support vector machine is used for multi-class classification. This work reports three experimental results for multi-class ship classification problem. First experiment trains on a synthetic image data-set and tests on a real image data-set, and obtained accuracy is 87.8%. Second experiment trains on a real image data-set and tests on a separate real image data-set, and obtained accuracy is 87.8%. Last experiment trains on real + synthetic image data-sets (combined data-set) and tests on a separate real image data-set, and obtained accuracy is 93.3%.
In this paper, we proposed a discrete cosine transform (DCT)-based attenuation and accentuation method to remove lighting effects on face images for facilitating face recognition task under varying lighting conditions...
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ISBN:
(纸本)9780819494344
In this paper, we proposed a discrete cosine transform (DCT)-based attenuation and accentuation method to remove lighting effects on face images for facilitating face recognition task under varying lighting conditions. In the proposed method, logorithm transform is first used to convert a face image into logarithm domain. Then discrete cosine transform is applied to obtain DCT coefficients. The low-frequency DCT coefficients are attenuated since illumination variations mainly concentrate on the low-frequency band. The high-frequency coefficients are accentuated since when under poor illuminations, the high-frequency features become more important in recognition. The reconstructed log image by inverse DCT of the modified coefficients is used for the final recognition. Experiments are conducted on the Yale B database, the combination of Yale B and Extended Yale B databases and the CMU-PIE database. The proposed method does not require modeling and model fitting steps. It can be directly applied to single face image, without any prior information of 3D shape or light sources.
Many published machinevision algorithms are designed to be real-time and fully automatic with low computational complexity. These attributes are essential for applications such as stereo robotic vision. Motion Pictur...
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ISBN:
(纸本)9781424479948
Many published machinevision algorithms are designed to be real-time and fully automatic with low computational complexity. These attributes are essential for applications such as stereo robotic vision. Motion Picture Digital visual Effect facilities, however, have massive computation resources available and can afford human interaction to initialise algorithms and to guide them towards a good solution. On the other hand, motion pictures have significantly higher accuracy requirements and other unique challenges. Not all machinevision algorithms can readily be adapted to this environment. In this paper we outline the requirements of visual effects and indicate several challenges involved in using imageprocessing and machinevision algorithms for stereo motion picture visual effects.
The earlier papers on SKIPSM (Separated-Kernel imageprocessing using finite State machines) concentrated mainly on implementations using pipelined hardware. Because of the potential for significant speed increases, t...
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ISBN:
(纸本)0819426377
The earlier papers on SKIPSM (Separated-Kernel imageprocessing using finite State machines) concentrated mainly on implementations using pipelined hardware. Because of the potential for significant speed increases, the technique has even more to offer for software implementations. However, the gigantic structuring elements (e.g., 51x51 in one pass) readily available in binary morphology using SKIPSM are not practical in grey-level morphology. Nevertheless, useful structuring element sizes can be achieved. This paper describes two such applications: dilation with a 7x7 square and a 7x7 octagon. Previous 2-D SKIPSM implementations had one row machine and one column machine. Two of the implementations described here follow this pattern, but the other has four machines: row, column, and the two 45-degree diagonals. In operation, all of these are one-pass algorithms: The next pixel is ''fetched'' from the input device, the two (or four) machines are updated in turn, and the resulting output pixel is written to the output device. All neighborhood information needed for processing is encoded in the state vectors of the finite-state machines. Therefore, no intermediate image stores are needed. Furthermore, even the input and output image stores can be eliminated if the image processor can keep up with the input pixel rate. Comparisons are provided between these finite-state-machine implementations and conventional implementation of the 2-step and 4-step decompositions, all based on the same structuring elements.
A machinevision system used for quantitative analysis of the uniformity of powder blending has been built at the CAIP center of Rutgers University. A wide variety of instruments are used in the system in order to per...
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ISBN:
(纸本)0819423106
A machinevision system used for quantitative analysis of the uniformity of powder blending has been built at the CAIP center of Rutgers University. A wide variety of instruments are used in the system in order to perform the imageprocessing algorithms required. This paper will introduce the system, focusing on the high speed imageprocessing hardware configurations and discussing the scheme for developing the software to manage this comprehensive system.
image retrieval tools can assist people in making efficient use of digital image collections;also it has become imperative to find efficient methods for the retrieval of these images. Most imageprocessing algorithms ...
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ISBN:
(纸本)9781467361842
image retrieval tools can assist people in making efficient use of digital image collections;also it has become imperative to find efficient methods for the retrieval of these images. Most imageprocessing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In very big image databases, imageprocessing takes very long time for run on a single core processor because of single thread execution of algorithms. GPU is more common in most imageprocessingapplications due to multithread execution of algorithms, programmability and low cost. In this paper we implement color moments and texture based image retrieval ( entropy, standard deviation and local range) in parallel using CUDA programming model to run on GPUs. These features are applied to search images from a database which are similar to a query image. We evaluated our retrieval system using recall, precision, and average precision measures. Experimental results showed that parallel implementation led to an average speed up of 144.67xover the serial implementation when running on a NviDIA GPU GeForce GT610M. Also the average precision and the average recall of proposed method are 61.968% and 55% respectively.
Saliency map is a central part of many visual attention systems, particularly during learning and control of bottom-up attention. In this research we developed a hardware tool to extract saliency map from a video sequ...
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ISBN:
(纸本)9781467361842
Saliency map is a central part of many visual attention systems, particularly during learning and control of bottom-up attention. In this research we developed a hardware tool to extract saliency map from a video sequence. Saliency map is obtained by aggregating primary features of each frame, such as intensity, color, and lines orientation, along with temporal difference. The system is designed to provide both high speed and acceptable accuracy for real-time applications, such as machinevision and robotics. A versatile Verilog model for realization of the video processing system is developed, which can easily be mapped and synthesized on various FPGA or ASIC platforms. The proposed parallel hardware can process over 50 million pixels in a second, which is about 2x faster than the state-of-the-art designs. Experimental results on sample images justify the applicability and efficiency of the developed system in real-time applications.
This paper introduces the structure and operation mode of automatic production line based on the actual situation of laser quenching automatic production line of tool in enterprises. Robot vision integrates workpiece ...
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ISBN:
(纸本)9781665464680
This paper introduces the structure and operation mode of automatic production line based on the actual situation of laser quenching automatic production line of tool in enterprises. Robot vision integrates workpiece positioning coordinates with robot coordinates to realize the positioning and grasping function of robot through machinevision. Focus on OpenCV imageprocessing methods. This paper describes its principle and possible problems from the aspects of system structure, robot coordinate calibration, visual identification and positioning and software design.
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