Watershed transformation is used in morphological image segmentation. This transformation could be considered as a topographic region growing method. Recently, fast watershed algorithms have been proposed for general ...
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ISBN:
(纸本)0819414751
Watershed transformation is used in morphological image segmentation. This transformation could be considered as a topographic region growing method. Recently, fast watershed algorithms have been proposed for general purpose computers. They are based on immersion simulations of the image surface, which is considered as a topographic relief. In such a model, the greylevel values of pixels stand for altitude values on the relief. In this paper, the operation of the present fast watershed algorithms is analyzed and a new extension is proposed. Drawbacks of the present algorithms are pointed out, studied, and illustrated with test images. These problems lead, in several cases, to a loss of information about image details and structures or even to unprocessed areas in the image. The new watershed algorithm overcomes these deficiencies and preserves more information about image details. The new algorithm is based on a split-and-merge scheme. It constantly monitors the presence of isolated areas during the immersion simulation, considering them as new catchment basins. Application of the split-and-merge watershed algorithm to marker-based image segmentation is discussed.
In this paper, a comprehensive set of fast algorithms for computing granulometries in binary images is first proposed: linear granulometries (i.e., granulometries based on openings with line segments) constitute the e...
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ISBN:
(纸本)081941624X
In this paper, a comprehensive set of fast algorithms for computing granulometries in binary images is first proposed: linear granulometries (i.e., granulometries based on openings with line segments) constitute the easiest case, and are computed using image `run-length'. The 2D case (granulometries with square or `diamond'-shaped structuring elements, or granulometries with unions of line-segments at different orientations) involves the determination of opening functions or granulometry functions. The grayscale case is then addressed, and a new algorithm for computing grayscale linear granulometries is introduced. This algorithm is orders of magnitude faster than any previously available technique. The techniques introduced in this paper open up a new range of applications for granulometries, examples of which are described in the paper.
Automatic detection and segmentation of microcalcifications may be achieved by application of algorithmic techniques or by use of artificial neural networks. We selected two neural network architectures and implemente...
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ISBN:
(纸本)081941462X
Automatic detection and segmentation of microcalcifications may be achieved by application of algorithmic techniques or by use of artificial neural networks. We selected two neural network architectures and implemented object detection techniques on them. Further we have developed two algorithmic approaches to segment microcalcifications. In the first algorithm, thresholding of local image gray level histogram is used for object segmentation. In the first pass each object is labeled and object boundaries are marked but they are not segmented from the background. In the second pass the discontinuities due to region boundaries are corrected for, by allocating a unique threshold value for each object commensurate with the local background. In an alternative algorithm we employ edge detection to identify the pixels that may potentially belong to microcalcifications. Region growing techniques are then applied and the resulting segmented objects are subjected to tests involving shape, size and gradient.
The paper considers and classifies the possible ways for construction of technology to convert document images into a geographic information system or CAD representation. Three basic document types are considered. The...
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ISBN:
(纸本)081941476X
The paper considers and classifies the possible ways for construction of technology to convert document images into a geographic information system or CAD representation. Three basic document types are considered. The image types on every step of the interpretation technology are extracted and described. The different variants of the technology are considered depending on the type of an initial document and algorithms used. The classification of eleven known in literature technologies is given. Our experience in the realization of technology variants is shown.
We present here an algorithm which performs radar cross-section estimation by using techniques based on simulated annealing. Standard simulated annealing approaches to image restoration attempt to categorize each imag...
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ISBN:
(纸本)0819415472
We present here an algorithm which performs radar cross-section estimation by using techniques based on simulated annealing. Standard simulated annealing approaches to image restoration attempt to categorize each image element as belonging to one of a small number of predefined image states or values. This is restrictive for tasks such as radar cross-section estimation and we present here an algorithm which is capable of producing a real-valued output. This is achieved by introducing an edge detection stage into the simulated annealing process. The action of the annealing algorithm may be viewed as a filter which adapts to local image structure. We present results which demonstrate this behavior and in so doing allow us to estimate the residual noise levels we might expect.
An important first step in diagnosis and treatment planning using tomographic imaging is differentiating and quantifying diseased as well as healthy tissue. One of the difficulties encountered in solving this problem ...
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ISBN:
(纸本)081941462X
An important first step in diagnosis and treatment planning using tomographic imaging is differentiating and quantifying diseased as well as healthy tissue. One of the difficulties encountered in solving this problem to date has been distinguishing the partial volume constituents of each voxel in the imagevolume. Most proposed solutions to this problem involve analysis of planar images, in sequence, in two dimensions only. We have extended a model-based method of image segmentation which applies the technique of iterated conditional modes in three dimensions. A minimum of user intervention is required to train the algorithm. Partial volume estimates for each voxel in the image are obtained yielding fractional compositions of multiple tissue types for individual voxels. A multispectral approach is applied, where spatially registered data sets are available. The algorithm is simple and has been parallelized using a dataflow programming environment to reduce the computational burden. The algorithm has been used to segment dual echo MRI data sets of multiple sclerosis patients using lesions, gray matter, white matter, and cerebrospinal fluid as the partial volume constituents. The results of the application of the algorithm to these datasets is presented and compared to the manual lesion segmentation of the same data.
For many real-time and scientific applications, it is desirable to perform signal and imageprocessingalgorithms by means of special hardware with very high speeds. With the advent of vLSI technology, large collectio...
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ISBN:
(纸本)0819416207
For many real-time and scientific applications, it is desirable to perform signal and imageprocessingalgorithms by means of special hardware with very high speeds. With the advent of vLSI technology, large collections of processing elements, which cooperate with each other to achieve high-speed computation, have become economically feasible. In such systems, some level of fault tolerance must be obtained to ensure the validity of the results. Fermat number transforms (FNT's) are attractive for the implementation of digital convolution because the computations are carried out in modular arithmetic which involves no round-off error. In this paper we present a fault tolerant linear array design for FNT by adopting the weighted checksum approach. The results show that the approach is ideally suited to the FNT since it offers fault tolerance, with very low cost, free from round-off error and overflow problems.
This paper presents an edge detection algorithm using Hopfield neural network. This algorithm brings up a new concept which is different from those conventional differentiation operators, such as Sobel and Laplacian. ...
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ISBN:
(纸本)0819415472
This paper presents an edge detection algorithm using Hopfield neural network. This algorithm brings up a new concept which is different from those conventional differentiation operators, such as Sobel and Laplacian. In this algorithm, an image is considered a dynamic system which is completely depicted by an energy function. In other words, an image is described by a set of interconnected neurons. Every pixel in the image is represented by a neuron which is connected to all other neurons but not to itself. The weight of connection between two neurons is described as being a function of contrast of gray-level values and the distance between pixels. The initial state of each neuron represents the normalized gray-level value of the corresponding pixel in the original image. As a result of Hopfield network analysis, output of neurons is modified until the convergence. Even though the outputs are analog, they are close to zero in all regions except edges where the corresponding neurons have near 1.0 output values. A robust threshold on the output level of the converged network can be easily set up at 0.5 level to extract edges. The experimental results are presented to show the effectiveness and capability of this algorithm.
This paper discusses high-speed array implementations of two imageprocessingalgorithms, namely the 'Hough transform for Detection of line segments', and 'Backprojection in CT image reconstruction'. A...
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This paper discusses high-speed array implementations of two imageprocessingalgorithms, namely the 'Hough transform for Detection of line segments', and 'Backprojection in CT image reconstruction'. A multi-chip-module (MCM) construction is proposed consisting of three types of chips, a high speed multi-function nonlinear chip, a flexible Multiply-Accumulate chip, and an image kernel chip. Called v-array, it can be configured to have eight HOUGH modules, so as to produce the Hough transform of a 1024 × 1024 image in an estimated 13 ms in 2.0 micron CMOS technology (6.6 ms in 1.0 micron CMOS technology). Similarly, a v-array MCM can accommodate eight CT modules, which can produce the backprojected image in 209 ms in 2.0 micron CMOS technology (105 ms in 1.0 micron CMOS technology). To gain a significant speed advantage, we have developed an advanced multi-function cell for performing any one of four nonlinear operations: (1) square-root, (2) reciprocal, (3) sine/cosine, and (4) arctangent - - all realized in a single chip, accessible on a selectable basis. A 16 bit four-function 'one cycle' vLSI chip, fabricated in 2.0 micron CMOS technology, is presently available which outputs a new result every clock cycle. Using this nonlinear cell and two other cells, an application level Hough transform module and a CT module are presented.
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