We propose an efficient approach towards the solution of the de-palletizing problem, based on active vision. We describe a system comprising an industrial robot and a time of flight laser sensor, which performs the de...
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ISBN:
(纸本)0780365763
We propose an efficient approach towards the solution of the de-palletizing problem, based on active vision. We describe a system comprising an industrial robot and a time of flight laser sensor, which performs the depalletizing task in real time, and independently of lighting conditions. In our case, the target objects are solid boxes of known identical dimensions, neatly layered but with arbitrary orientation within a layer, which are all placed on a platform. The layered structure of the target platform allows for 2D imagery. The system locates the position of the boxes by tracking one of the corners they expose to the laser source. The system locates the desired corners by applying the scan line approximation technique, adapted to fit the needs of our application, to the 2D input data. The advantages of our system over existing applications are its simplicity, robustness, speed and ease of installation.
In this paper, we propose a video watermarking technique to hide copyright information in MPEG motion vector. In this method, watermark is embedded in larger value motion vectors, and specially in the less phase angle...
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In this paper, we propose a video watermarking technique to hide copyright information in MPEG motion vector. In this method, watermark is embedded in larger value motion vectors, and specially in the less phase angle changed component. Then, the motion vector is modified into a new bitstream from which the watermark information can be easily retrieved. From the experimental results, it indicates that to embed watermark in motion vector has the advantage of little degrading the video quality, little influence on the MPEG decoding speed, capability to embed watermark in a short video sequence, and can be used to watermark on both the uncompressed and compressed video sequence.
Fingerprint recognition and verification are often based on local fingerprint features, usually ridge endings or terminations, also called minutiae. By exploiting the structural uniqueness of the image region around a...
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Fingerprint recognition and verification are often based on local fingerprint features, usually ridge endings or terminations, also called minutiae. By exploiting the structural uniqueness of the image region around a minutia, the fingerprint recognition performance can be significantly enhanced. However, for most fingerprint images the number of minutia image regions (MIRs) becomes dramatically large, which imposes - especially for embedded systems - an enormous memory requirement. Therefore, we are investigating different algorithms for compression of minutia regions. The requirement for these algorithms is to achieve a high compression rate (about 20) with minimum loss in the matching performance of minutia image region matching. We investigate the matching performance for compression algorithms based on the principal component and the wavelet transformation. The matching results are presented in form of normalized ROC curves and interpreted in terms of compression rates and the MIR dimension.
Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage a...
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ISBN:
(纸本)0769512631
Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage approach is addressed to segment unconstrained handwritten Chinese character strings. A string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. At the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. Geometric features are extracted and fuzzy decision rules learned from examples are used to evaluate the segmentation paths. By using this two-stage segmentation approach, we can achieve both good performance and efficiency in segmenting unconstrained handwritten Chinese characters.
Segmentation of connected handwritten Chinese characters is a very difficult task in document image analysis. In this paper, a novel algorithm based on stroke analysis and background thinning is proposed to segment co...
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An algorithm to group edge points into digital line segments with Hough transformation is described in this paper. The edge points are mapped onto the parameter domain dis-cretked at specific intervals, on which peaks...
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The use of plane graphs for the description of image structure and shape representation poses two problems : (1) how to obtain the set of vertices, the set of edges and the incidence relation of the graph, and (2) how...
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An association rule typically strives for discovering a dependency among attributes with respect to the externally defined parameters like support threshold and confidence threshold. As an important database discovery...
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ISBN:
(纸本)3540679251
An association rule typically strives for discovering a dependency among attributes with respect to the externally defined parameters like support threshold and confidence threshold. As an important database discovery method, the kernel of association rule mining is the acquisition of large itemsets. It is an important field of data mining to represent the support and confidence of items that are purchased together in supermarket domain. In this paper, a novel limited concept lattice is first proposed for the transaction data itemsets modeling. Concept lattice is a form of a concept hierarchy in which each node represents a subset of objects (extent) with their common properties (intent). The Hasse diagram of the lattice represents a generalization/specialization relationship between the concepts. Therefore, the lattice and Hasse diagram corresponding to a set of objects described by some properties can be used as an effective tool for symbolic data analysis and knowledge acquisition. Based on this lattice structure, an algorithm, LCLL, is presented to incrementally generate large itemsets visually. The algorithm works by means of attaching frequency information to each lattice node, the corresponding support measure can be obtained with the limited lattice. Besides, the edges in the Hasse diagram of the new lattice must be modified: the generator of a new node is always its child, and original parent of the generator is updated. When a node is deleted till the frequency value turns to zero, the node and the edges between its parents and children are not deleted, but tagged. The key point lies in adding edges when searching for the new node’s parents, the large itemsets can be obtained by judging whether the cardinal and frequency value of the node exceeds the threshold or not. And accordingly, association rules can be identified. The approach is especially efficient when the database is dynamically updated (insertion, deletion or simultaneous insertion and deletion
Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In ...
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Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.
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