Two-dimensional Binary Images Research Articles

Nonparametric hierarchical Hausdorff distance matching algorithm

A Hausdorff distance (HD), which is defined between two point sets in two-dimensional (2-D) binary images and does not require us to establish correspondences, is one of common measures used for object matching. The proposed hierarchical HD (HHD) matching algorithm, based on coarse-to-fine matching, reduces the computational complexity greatly by using the pyramidal structures that consist of a distance transform (DT) map pyramid and an edge pyramid. in the proposed HHD matching, an automatic thresholding method is presented to select candidate positions at each level, in which the threshold value is determined based on the property between adjacent levels of a DT map pyramid. Computer simulation with real images and noisy images shows that the proposed HHD algorithm yields matching results similar to those achieved by the conventional HD algorithm with greatly reduced computational complexity.

Fast parallel shrinking to residues

The problem of shrinking the connected components of binary images to small residues is addressed. A new parallel algorithm is presented with the lowest known worst case time complexity as measured by iteration counts, i.e., ?(nc+nr)/2? iterations where the foreground of the image is contained within a rectangular region of size ncxnr pixels. The new algorithm also demonstrates superior average iteration counts in comparison with other shrinking algorithms on test images. The new algorithm uses a fully parallel application of an operator with an 8 pixel support. It reduces all connected components in any two-dimensional (2D) binary image to certain small 1, 2, or 3 pixel residues. It is potentially useful for component counting, as a fundamental step in connected component labeling algorithms implemented with fine grain realizations in 2D mesh computing architectures, and in other applications requiring preservation of foreground topology (connectivity).

Relationship between plain radiographic patterns and three- dimensional trabecular architecture in the human calcaneus.

The purpose of this study was to determine the relationship between three-dimensional (3D) trabecular structure and two-dimensional plain radiographic patterns. An in vitro cylinder of human calcaneal trabecular bone was three-dimensionally imaged by micro-CT using synchrotron radiation, at 33.4 micrometer resolution. The original 3D image was processed using 14 distinct sequences of morphologic operations, i.e., of dilations and erosions, to obtain a total of 15 3D models or images of calcaneal trabecular bone. These 15 models had distinct densities (volume fractions) and architectures. The 3D structure of each calcaneal model was assessed using mean intercept length (fabric), by averaging individual fabric measurements associated with each medial-lateral image slice, and determining the relative anisotropy, R(3D), of the structure. A summated pattern or plain radiograph was also computed from the 3D image data for each calcaneal model. Each summated pattern was then locally thresholded, and the resulting two-dimensional (2D) binary image analyzed using the same fabric analysis as used for the 3D data. The anisotropy of the 2D summated pattern was denoted by R(x-ray). The volume fractions of the 15 models ranged from 0.08 to 0.19 with a mean of 0. 14. The medial-lateral anisotropies, R(3D), ranged from 1.38 to 2.54 with a mean of 1.88. The anisotropy of the 2D summated patterns, R(x-ray), ranged from 1.35 to 2.18 with a mean of 1.71. The linear correlation of the 3D trabecular architecture, R(3D), with the radiographic trabecular architecture, R(x-ray), was 0.99 (p<0.0001). This study shows that the plain radiograph contains architectural information directly related to the underlying 3D structure. A well-controlled sequential reproducible plain radiograph may prove useful for monitoring changes in trabecular architecture in vivo and in identifying those individuals at increased risk of osteoporotic fracture.

From fractal analysis along a line to fractals on the plane

Self-similar fractals are useful models for soil solid and pore sets. The scaling properties of these fractals along a line and across an area can be described by the fractal dimensions. One method, for estimating the soil areal fractal dimension from the solid and pore set distributions along the lines, was proposed and tested with real macro- and micromorphological data on three soils of Mexico. The soil areal fractal dimension ( D a) was compared with the soil mass fractal dimension ( D m) estimated by two-dimensional binary image analysis, separately for solids and pores. Both methods are based on the box-counting technique and are suitable for determining the soil `box' or `capacity' fractal dimension, that seems to be apt to estimate the alternative filling of an area by a fractal set of solids and pores. This paper examines the relations between the fractal dimensions obtained along a line, across an area and directly from the image. Analysis of D a and D m data seems to suggest that both soil genesis and management practice can contribute to areal fractal dimension dynamics. It was shown that fractal dimensions are useful parameters able to monitor tillage influence on soil properties and to estimate the degree of soil compaction.

An algorithm for affine transformation of three‐dimensional objects registered with run format

The authors have previously proposed an efficient affine transformation algorithm for the two-dimensional binary image, where the image is represented by the run format called PXY table and the transformation is executed combining the skew and the transpose manipulations. This paper proposes a new affine transformation algorithm for the three-dimensional object (three-dimensional binary image) represented by the three-dimensional run format, called SPXY table. The SPXY table is composed by stacking the two-dimensional PXY tables. The affine transformation on the SPXY table is realized as a combination of the three-dimensional skew and the transpose manipulations, as an extension of the case of the two-dimensional PXY table. As the result of experiment, it is shown that the proposed method is faster, by a factor of 36 to 389, than the primitive method which applies the transformation to each voxel. It is also shown that the CPU time for the affine transformation by the proposed method is proportional to the number of runs in the representation of the three-dimensional object. The result of the affine transformation by the proposed method contains an error, which may be greater than the rounding error when the result is converted to an integer by rounding the subdecimal. The error analysis is applied to the three-dimensional rotation, which is used most frequently among the affine transformations. As a result, it is seen that the absolute error of each coordinate in the proposed method is 1.4 at the maximum. © 1998 Scripta Technica. Syst Comp Jpn, 29(3): 18–27, 1998

A 0.8-μm CMOS two-dimensional programmable mixed-signal focal-plane array processor with on-chip binary imaging and instructions storage

This paper presents a CMOS chip for the parallel acquisition and concurrent analog processing of two-dimensional (2-D) binary images. Its processing function is determined by a reduced set of 19 analog coefficients whose values are programmable with 7-b accuracy. The internal programming signals are analog, but the external control interface is fully digital. On-chip nonlinear digital-to-analog converters (DAC's) map digitally coded weight values into analog control signals, using feedback to predistort their transfer characteristics in accordance to the response of the analog programming circuitry. This strategy cancels out the nonlinear dependence of the analog circuitry with the programming signal and reduces the influence of interchip technological parameters random fluctuations. The chip includes a small digital RAM memory to store eight sets of processing parameters in the periphery of the cell array and four 2-D binary images spatially distributed over the processing array. It also includes the necessary control circuitry to realize the stored instructions in any order and also to realize programmable logic operations among images. The chip architecture is based on the cellular neural/nonlinear network universal machine (CNN-UM). It has been fabricated in a 0.8-/spl mu/m single-poly double-metal technology and features 2-/spl mu/s operation speed (time required to process an image) and around 7-b accuracy in the analog processing operations.

Linear time Euclidean distance transform algorithms

Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a two-dimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels in the image. The first algorithm, which is of primarily theoretical interest, constructs the complete Voronoi diagram. The second, more practical, algorithm constructs the Voronoi diagram where it intersects the horizontal lines passing through the image pixel centers. Extensions to higher dimensional images and to other distance functions are also discussed. >

223 一様流中で急回転急停止する中空円筒の内外流れのPIVによる計測

The purpose of the present study is to measure and investigate unsteady flows inside and outside a hollow circular cylinder with sudden rotating and stopping in a uniform flow and finally in order to obtain some fundamental data about the virtual mass effect. The flows inside and outside a hollow cylinder which is made of transparent acrylic resin are visualized by the particle tracer technique and analyzed using the PIV technique based on the two-dimensional binary image cross-correlation method. As a result, the unsteady whole field flows are discussed.

Characterization of microfiltration membranes by image analysis of electron micrographs.: Part I. Method development

A series of cellulosic microfiltration membranes in the range of rated pore size 0.025–1.2 micrometer was examined by scanning electron microscopy (SEM) coupled to computerized quantitative image analysis (QIA). Definition of pore-related size and shape parameters as well as procedures used for obtaining their numerical values are presented. Effects of image contrast, resolution and grey-level segmenting threshold are described. Ambiguities and limitations involved in reduction of a three-dimensional structure into a two-dimensional binary image are discussed.

Gray-image processing using optical array logic

A method for digital image processing that uses optical array logic (OAL) is presented. Parallel thresholding and digital filtering are demonstrated. OAL is a promising computational paradigm for digital optical computing based on parallel neighborhood operations for two two-dimensional binary images. In the proposed method, virtual processing elements are assumed on an image plane and a gray pixel in an original gray image is stored in each processing element. Efficient gray-image processing can be achieved by data manipulation in the virtual processing elements and in the data communication among them by using OAL. Several simulation results are presented. Finally, hardware requirements for the developed algorithms and their capabilities are discussed.

AUTOMATIC PLANT FEATURE IDENTIFICATION ON GERANIUM CUTTINGS USING MACHINE VISION

ABSTRACT A machine vision technique was developed which analyzes a two-dimensional binary image of a singulated geranium cutting and identifies the branching stem structure, including main stem and petioles. The analysis technique was based on creation of a directed graph data structure which contains information required to rapidly perform plant part identification. Size, shape, and location data were utilized to classify objects as particular plant features. Evaluation of the image analysis technique indicated good characterization of the binary structure of geranium cuttings in a timely manner as required for use in a robotic workcell. Identification of the main stem, petioles, growth tip, and geometry of the interconnections of the plant parts was successfully performed. Overlapping sections (e.g., petiole crossings) and occlusions (e.g., leaves over stem segments) contributed to identification errors.

A parallel architecture and algorithms for optical computing

A new parallel optical architecture is introduced for computing massively data-parallel applications. The system processes two-dimensional binary images as basic computational entities. The processing is based on the optical symbolic substitution (SS) technique. New optical SS rules are introduced as well as a technique for designing and mapping data-parallel algorithms onto the proposed architecture. Implementation issues and performance analysis are also considered.

Reconstruction of three-dimensional surfaces from two-dimensional binary images

The authors describe a method for reconstruction of three-dimensional visible and invisible opaque surfaces using moving shadows. An object whose shape is to be determined is placed on a reference surface. A beam of substantially parallel rays of light is projected at the object at a set of different angles relative to the reference surface. Using a camera which is placed above the reference surface, the shadows cast by the object for each angle are transferred to a computer. A three-dimensional binary level shadow diagram (3DBL shadowgram) is formed and analyzed. The shadowgram has some features which make the reconstruction very simple: a section of the 3DBL shadowgram, referred to as a 2DBL shadowgram, can be used to determine the heights of points of the object to be reconstructed. Further analysis of some curves of the shadowgram can be used for the partial reconstruction of invisible surfaces. A set of experimental results to test the effects of the threshold, camera resolution, and the number of pictures demonstrates the robustness and usefulness of the method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Synthesis of two-dimensional binary images through band-limited systems: a slicing method

A method is presented for solving the problem of synthesis of a two-dimensional (2-D) band limited function with prescribed level crossing. This method relies on decomposing a 2-D band limited function into the sum of products of one-dimensional (1-D) band limited functions along two orthogonal directions. The 1-D functions in one direction represent slices of the desired 2-D function and have zero crossings at the desired locations. They are produced by inserting and deleting zeros in a known band limited function (a sinc function). The orthogonal 1-D functions are used as interslice interpolation functions. The generated 2-D function is band-limited and has correct zeros at the slices. Its zeros between slices may not be correct, but the interslice distance can be made arbitrarily small. Nonuniform slicing can be used to improve the resolution of the approximations. Interpolation functions for the nonuniform slices are generated by the same method used to produce the slices.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The Use of Linear Quadtrees in a Numerical Problem

Linear quadtrees have proved to be a useful structure for representing quadrants’ subdivisions and groupings in association with the encoding of two-dimensional binary images. In this paper it is shown that linear quadtrees can also be successfully applied to the memory management of the class of polynomial solvers proposed by P. Henrici [Applied and Computational Complex Analysis, Vol. 1, John Wiley, 1974], [in Constructive Aspects of the Fundamental Theorem of Algebra, Wiley-Interscience, 1969]. The problem of evaluating “the bounding box” of a connected region, given as a linear quadtree, is also considered, and an algorithmic solution presented.

Feature Extraction and Selection for Pattern Recognition of Two-Dimensional Hydrometeor Images

Abstract New feature extraction techniques are developed for two-dimensional binary images of ice particles and raindrops. These features are employed in the statistical classification of these patterns into one of seven basic hydrometeor shapes. These images have been recorded by an airborne two-dimensional probe in order to provide information leading to an understanding of important physical processes in clouds. Minimum average probability of classification error is employed as the performance criterion with informal minimization of computing time. A synthetic image set was generated to develop feature extraction techniques. Moment normalization and rotation normalization are employed to convert all images to a common size and orientation. Ten time domain features are explored including a new development (circular deficiency) and a new application (cross correlation). Three frequency domain features are investigated including a new Fourier descriptor (centroid distance). An original method of reducing ...

A method for the optimal design of a class of pattern recognition systems

Easily implemented measurements which allow an equal variance in all portions of a pattern are made on single rows and columns of a two-dimensional binary image of the pattern. An optimal minimum set of measurements for each size binary image is determined by solving a prime implicant chart. Application of an economic principle determines the best system. A simple example is presented to demonstrate the method. The best system for a set of 52 characters is determined using the method. Results indicate that a maximum allowable variation in any letter is 30.9 per cent, regardless of binary image size. An hypothesis relating character set size and character similarity is stated.

Repair stations for spacecraft

This paper describes the use of ultrasonic guided waves for identifying the mass loading due to underwater limpet mines on ship hulls. The Dynamic Wavelet Fingerprint Technique (DFWT) is used to render the guided wave mode information in two-dimensional binary images because the waveform features of interest are too subtle to identify in time domain. The use of wavelets allows both time and scale features from the original signals to be retained, and image processing can be used to automatically extract features that correspond to the arrival times of the guided wave modes. For further understanding of how the guided wave modes propagate through the real structures, a parallel processing, 3D elastic wave simulation is developed using the finite integration technique (EFIT). This full field, technique models situations that are too complex for analytical solutions, such as built up 3D structures. The simulations have produced informative visualizations of the guided wave modes in the structures as well as mimicking directly the output from sensors placed in the simulation space for direct comparison to experiments. Results from both drydock and in-water experiments with dummy mines are also shown.