A new technique is described fast ″scan-along″ computation of piecewise linear approximations of digital curves in 2-space. Our method is derived from earlier work on the theory of minimum-perimeter polygonal approx...
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A new technique is described fast ″scan-along″ computation of piecewise linear approximations of digital curves in 2-space. Our method is derived from earlier work on the theory of minimum-perimeter polygonal approximations of digitized closed curves. It is demonstrated that the specialization of this technique to the cases where the error is measured as a) the largest Hausdorff-Euclidean distance between the approximation and the given digitized curve, and b) the largest vertical distance between the approximation and a corresponding point on the given digitized curve.
An evaluation is made of the performance of two segmentation algorithms. The extreme difficulty of evaluating the quality of such segmentations, particularly on images of natural scenes, is discussed. The first algori...
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An evaluation is made of the performance of two segmentation algorithms. The extreme difficulty of evaluating the quality of such segmentations, particularly on images of natural scenes, is discussed. The first algorithm involves the symbolic labelling of pixels based upon cluster analysis of histograms and a probabilistic relaxation labelling algorithm. It is shown that serious segmentation problems are overcome when the algorithm is properly localized to overlapping subimages of data. Both algorithms are applied to fairly challenging machine-generated test images, as well as a natural image.
A segmentation is done on a monochrome 256 multiplied by 256 image using only texture information generated by local extreme measurements. The number of extrema of various sizes are counted over a local region and the...
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A segmentation is done on a monochrome 256 multiplied by 256 image using only texture information generated by local extreme measurements. The number of extrema of various sizes are counted over a local region and these numbers are used to separate the regions. The use of texture edge information in the local averaging process is discussed.
We present a method to locate an `object' in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color, which permits the use of color-space pr...
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ISBN:
(纸本)081863880X
We present a method to locate an `object' in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color, which permits the use of color-space processing. A new method is presented, which exploits more information than the previous Backprojection Algorithm of Swain and Ballard at a competitive complexity. Precisely, the new algorithm is based on matching local histograms with the model, instead of directly replacing pixels with a confidence that they belong to the object. We prove that a simple version of this algorithm degenerates into Backprojection in the worst case. In addition, we show how to estimate the scale of the model. We also propose the use of co-occurrence histograms to deal with cases where important color variations can be expected. Results are shown on pictures digitized from the famous `Waldo' books.
An algorithm for extracting and segmenting surface descriptions from stereo images is presented. Compared with the advance of range image segmentation, the progress of surface segmentation from stereo images is slow. ...
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The objective of computer vision system is to outline the objects in a picture and label them with an appropriate interpretation. This study proposes a new paradigm for a modular computer vision system which is both d...
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The objective of computer vision system is to outline the objects in a picture and label them with an appropriate interpretation. This study proposes a new paradigm for a modular computer vision system which is both data directed and knowledge based. The system consists of three different types of units, two of which are associative data memories implemented as relational databases. The short term memory (STM) contains the raw color picture data and the most current interpretations and deductions about the original scene. The long term memory (LTM) contains a detailed model of the scene under consideration. A collection of analysis processors, each of which is specialized for a particular task can communicate with both of these memories.
This paper presents a new attempt at using augmented normalizing flows (ANF) for lossy image compression. ANF is a specific type of normalizing flow models that augment the input with an independent noise, allowing a ...
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ISBN:
(纸本)9781665448994
This paper presents a new attempt at using augmented normalizing flows (ANF) for lossy image compression. ANF is a specific type of normalizing flow models that augment the input with an independent noise, allowing a smoother transformation from the augmented input space to the latent space. Inspired by the fact that ANF can offer greater expressivity by stacking multiple variational autoencoders (VAE), we generalize the popular VAE-based compression framework by the autoencoding transforms of ANF. When evaluated on Kodak dataset, our ANF-based model provides 3.4% higher BD-rate saving as compared with a VAE-based baseline that implements hyper-prior with mean prediction. Interestingly, it benefits even more from the incorporation of a post-processing.network, showing 11.8% rate saving as compared to 6.0% with the baseline plus post-processing.
We present an image indexing method based on a hierarchical description of the density of each of the image classes in a given database. The method is similar in spirit to traditional agglomerative clustering procedur...
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ISBN:
(纸本)0769512720
We present an image indexing method based on a hierarchical description of the density of each of the image classes in a given database. The method is similar in spirit to traditional agglomerative clustering procedures but produces a complete mixture density, instead of a representative point, at each node of the indexing tree. Estimation of the density at a given node only requires knowledge of the mixture parameters of the children nodes, not the original data. The process is very flexible and efficient, therefore suited to problems involving large databases where existing groupings may have to be combined, or new groupings created, frequently. Experimental results show that the new indexing structure consistently outperforms a linear search when both efficiency and retrieval accuracy are taken into account.
In a previous paper, the authors present an O(kl multiplied by k2) depth-first tree search algorithm to find a montonic transformation such that the histogram of a transformed picture is closest to the desired histogr...
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In a previous paper, the authors present an O(kl multiplied by k2) depth-first tree search algorithm to find a montonic transformation such that the histogram of a transformed picture is closest to the desired histogram of a given picture in the L1 norm sense (least sum of absolute differences). The same problem using Ln norm is investigated in this paper. A breadth-first tree search algorithm with cut-off threshold is described, which has time complexity 0(k1 multiplied by k2).
A picture digitization grid based on logarithmic spirals rather than Cartesian coordinates is presented. Expressing this curvilinear grid as a conformal exponential mapping reveals useful imageprocessing.properties. ...
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A picture digitization grid based on logarithmic spirals rather than Cartesian coordinates is presented. Expressing this curvilinear grid as a conformal exponential mapping reveals useful imageprocessing.properties. The mapping induces a computational simplification that suggests parallel architectures in which most geometric transformations are effected by data shifting in memory rather than arithmetic on coordinates. These include fast, parallel noise-free rotation, scaling, and some projective transformations of pixel defined images. Conformality of the mapping preserves local picture-processing.operations such as edge detection.
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