Input Object Research Articles

3D surface cellular automata and their applications

This paper describes the generation and rendering of three-dimensional (3D) surface cellular automata (CA). Our model’s main advantage is that it gives direct texturing simulation based on the actual shape of anytriangulated input object. We first introduce general CA concepts and summarize works in the literature. We then describe our 3D surface CA method, emphasizing how it avoids potential problems in data structure and rendering steps. We then detail, two examples of specific 3D surface CA with their respective cell structures and corresponding computer graphics images.

3D surface cellular automata and their applications

This paper describes the generation and rendering of three-dimensional (3D) surface cellular automata (CA). Our model's main advantage is that it gives direct texturing simulation based on the actual shape of any triangulated input object. We first introduce general CA concepts and summarize works in the literature. We then describe our 3D surface CA method, emphasizing how it avoids potential problems in data structure and rendering steps. We then detail, two examples of specific 3D surface CA with their respective cell structures and corresponding computer graphics images. Copyright © 1999 John Wiley & Sons, Ltd.

A real-time pseudocolor encoding technique for the phase rate-of-change in the imaging system of microscope

A real-time white light stereo pseudocolor encoding technique for the phase rate-of-change in the imaging system of microscope is presented. It is analyzed by the theory of partially coherent light. The analytic results showed that the information about phase rate-of-change of the input object function is reflected in the output stereo pseudocolor image under given conditions and illuminated by incoherent source.

Declarative workflows that support easy modification and dynamic browsing

A new programming paradigm named "Vortex" is introduced for specifying a wide range of decision-making activities including, in particular, workflows. In Vortex workflows are specified declaratively. A particular emphasis is on "object-focused" workflows, i.e., workflows focused on how individual input objects should be processed within an organization. Such workflows arise commonly in practice, including insurance claims processing, and many electronic commerce applications, and in the area of Customer Care, e.g., web-based storefronts. Vortex workflows are "attribute-centric", because they are centered around how the attribute values for an input object are gathered and computed. Initially, only a few attributes of an input object have assigned values. During processing of the object, additional attribute values may be assigned by external modules, or by internal modules, including "decision modules". Decision modules include "attribute rules" that specify contributions to specific attribute values; these are combined with one of a broad family of available semantics. In Vortex, enabling conditions are used to determine what attributes should be evaluated. A novel choice-based execution model provides a general framework for optimization strategies. The use of enabling conditions, attribute rules and declarative semantics makes Vortex workflows easier to modify and refine than traditional, procedurally specified workflows. Vortex supports modularity and permits the natural intermixing of Vortex workflows with traditional, procedural workflows. The paper introduces a novel spreadsheet-like interface for dynamic browsing of Vortex executions.

ANALYSIS OF IMAGE-FORMING MECHANISM FOR A NOVEL STEREO PSEUDO COLOR MICROSCOPE

A novel stereo pseudo color real-time image-forming system of microscope is presented, and its cause is analyzed by the theory of partially coherent light. The analytic result shows that the distribution information about phase change of the input object function, under given conditions, is reflected in the output stereo pseudo color image while an incoherent light illuminates.

Microlens arrays produced with the help of the sampling filter

We describe a new method for microlens array generation based on the application of the imaging properties of the sampling filter. A binary amplitude mask corresponding to the transmittance of a lens is used as an input object. Its multiplied images, produced by the sampling filter with properly selected resolution, are characterized by the continuous distribution of intensity, which, when exposed in a phasephotosensitive material lead to the appearance of the microlens array. The specific, collective character of the imaging process results in great lens homogeneity. The technique offers wide design freedom and enables us to obtain lenses of long focal lengths. Numerical verification of the concept as well as experimental results are presented.

From Shape from Shading to Object Recognition

Recognition of objects is one of the main goals of computer vision. Several approaches have been proposed to solve this problem using 3-D shapes. In most of them it is assumed that the 3-D shape (depth map) is available. Several object recognition systems use range images to extract the 3-D shape. We present a method that uses a shape from shading algorithm to perform 3-D object recognition for simple objects. This method extracts the 3-D information from a single intensity image, then segments the object into regions. After computing the properties of the regions, it compares the input object with the model objects in the database. To test our method, several images with slightly different viewing angles of single objects are matched against five models in the database.

Analysis of the fractional Hilbert transform

The Hilbert transform is of interest for image-processing applications because it forms an image that is edge enhanced relative to an input object. Recently a fractional Hilbert transform was introduced that can select which edges are enhanced and to what degree the edge enhancement occurs. Although experimental results of this selective edge enhancement were presented, there was no explanation of this phenomenon. We analyze a one-dimensional fractional Hilbert transform acting on a one-dimensional rectangle function and show how it produces an output image that is selectively edge enhanced.

Parallel computing: a tool for image evaluation

The evaluation of the optical performance of optical systems by means of the diffraction patterns, bidimensional input objects composed of several object points, etc. consumes a huge amount of computing time. Furthermore, multiple-purpose optical systems that use the Fourier and image planes for different applications require evaluation and optimization on both planes, which also consumes a huge amount of computing time. A program to solve the computing time problem using parallel programming is presented. The program evaluates the image quality of a triplet camera lens and a radial gradient-refractive-index (GRlN) lens by tracing numerous rays from several object points distributed on the object plane. Using two Sparc Workstations, in parallel, this program can reduce the computing time almost to half that needed using only one machine.

Learning Nouns and Adjectives: A Connectionist Account

Why do children learn nouns such as cup faster than dimensional adjectives such as big? Most explanations of this phenomenon rely on prior knowledge of the noun-adjective distinction or on the logical priority of nouns as the arguments of predicates. In this article we examine an alternative account, one which relies instead on properties of the semantic categories to be learned and of the word-learning task itself. We isolate four such properties: The relative size, the relative compactness, and the degree of overlap of the regions in representational space associated with the categories, and the presence or absence of lexical dimensions (what colour) in the linguistic context of a word. In a set of five experiments, we trained a simple connectionist network to label input objects in particular linguistic contexts. The network learned categories resembling nouns with respect to the four properties faster than it learned categories resembling adjectives.

Direction sensing rotational filter for an optical correlator

The output of an optical correlator is sensitive to rotations of the input object. However, the correlator cannot distinguish the direction of this rotation (clockwise or counterclockwise). We introduce a rotation- ally sensitive multiplexed filter that senses both the direction and amount of rotation of the input object without employing iterative filter techniques. Our filter simultaneously forms three correlation outputs at three different spatial locations. Each output represents the correlation of the input ob- ject with a different rotated version of the reference object. Comparison of the three correlation outputs enables the direction and amount of ro- tation to be determined. This approach is insensitive to changes in the input object intensity because the various correlation peaks are formed simultaneously. Experimental results show an angular sensitivity of less than 0.5 deg. © 1998 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(98)00401-2) Subject terms: recognition techniques; alignment; correlators; filters; pattern rec- ognition.

Holographic memory with correlator based readout

The investigation of an inverted hybrid digital/optical VanderLugt type correlator based on a holographic memory is reported in this paper. A set of reference templates is stored in a photorefractive crystal (PRC) by angular hologram multiplexing. In the filter plane, a phase-modulating liquid crystal television (LCTV) serves as a phase-only input device. During the recognition process, which is based on the pure phase correlation, the reference templates are correlated sequentially with the input object. This correlator shows high sensitivity to object rotation, sharp correlation peaks, high light efficiency, and is fully shift-invariant in spite of the PRC thickness. The influences of the LCTV on the performance of the system are discussed and experimental results are shown.

Influence of flatness distortion on the output of a liquid-crystal-television-based joint transform correlator system

The use of liquid-crystal panels from a commercially available Sanyo video projector as spatial light modulators in a standard joint transform correlator system is investigated. It is found that the flatness distortion of the panels disturbs the output correlation signal in general. Since the reported solutions for the flatness corrections are either expensive (liquid gates) or suffer from low light efficiency (holographic techniques), we have investigated a possibility to minimize the influence of these distortions on the correlation output without flatness correction. First, we quantify optical flatness across the transparent panel area, and then we measure the effects of flatness distortion by changing the display location of the input objects and the resulting joint power spectrum. It is found that the correlation peak is 1 order of magnitude more sensitive to phase distortions of the input scene than to the same distortions of the joint power spectrum. Choosing the flattest location on the panel allows the utilization of the panels to be demonstrated through recognition of cuneiform inscription signs.

Fractional derivative Fourier plane filter for phase-change visualization

Fractional derivatives of two-dimensional images have been discussed theoretically in terms of Fourier optics and computer simulated. Filters that realize the half-order differentiation can be either complex or real. We prove, in terms of fractional calculus, that the semiderivative filter is useful for the visualization of phase changes in a phase object in such a way that the output-image intensity is directly proportional to the first derivative of the input object. We give computer-simulated results of one-dimensional semidifferentiating.

Feature space trajectory for distorted-object classification and pose estimation in synthetic aperture radar

Classification and pose estimation of distorted input objects are considered. The feature space trajectory representation of distorted views of an object is used with a new eigenfeature space. For a distorted input object, the closest trajectory denotes the class of the input and the closest line segment on it denotes its pose. If an input point is too far from a trajectory, it is rejected as clutter. New methods for selecting Fukunaga-Koontz discriminant vectors, the number of dominant eigenvectors per class and for determining training, and test set compatibility are presented.

Object-binarized phase-only matched filtering with dual liquid-crystal spatial light modulators

A real-time optical processing system with dual liquid-crystal spatial light modulators is constructed and used as both an amplitude-input device and a multilevel phase-only filter. Fourier analysis is given to show the performance of light efficiency, signal-to-noise ratio, and discrimination capability with the binarization of gray objects. The ratio of the dc power spectrum to the power spectra for input objects is introduced to incorporate the power spectrum into discrimination-capability evaluation. A numerical calculation is performed for gray-level and binarized amplitude-phase correlations. Improvement of the performance criteria has been achieved for an amplitude in a binary mode to a phase correlator. The higher the threshold level of the binarized objects is, the better performance criteria are produced. The effect of illumination over an input object on the autocorrelation maximum is experimentally investigated. Experimental results are presented to support the calculations.

A machine learning approach for acquiring descriptive classification rules of shape contours

We devise a method to generate descriptive classification rules of shape contours by using inductive learning. The classification rules are represented in the form of logic programs. We first transform input objects from pixel representation into predicate representation. The transformation consists of preprocessing, feature extraction and symbolic transformation. We then use FOIL which is an indictive logic programming system to produce classification rules. Experiments on two sets of data were performed to justify our proposed method.

Real-time phase-only matched filtering with dual liquid-crystal spatial light modulators

A matched filtering system with dual liquid-crystal spatial light modulators (LC-SLMs) which are used as an amplitude input and a phase-only filter (POF), respectively, has been constructed. A computer calculates peak intensities of an amplitude object-POF, a phase object-POF, an amplitude-matched spatial filter (MSF), and phase-MSF correlations. The input objects are characters in a binary amplitude or phase mode. The amplitude to POF correlation demonstrates highest discrimination among four kinds of the object-filter correlations. The experiments are real-time performed to produce the amplitude to POF correlation with dual LC-SLMs.

Parallel Threshold Voting

Voting on large collections of input objects is becoming increasingly important in data fusion, signal and image processing applications, learning algorithms, and distributed computing. To achieve high speed in voting, the multiple processing resources typically available in such applications should be utilized; hence the need for parallel voting algorithms. We develop efficient parallel algorithms for threshold voting which generalize and extend previous work on both sequential threshold voting and parallel majority voting. Our discussion centers on unweighted threshold (m-out-of-n) voting. However, we observe that under certain conditions, the results can be extended to efficient weighted threshold voting. We show how a known O(n)-time sequential algorithm for m-out-of-n voting can be parallelized through a simple divide-and-conquer strategy. When m = θ(n), the resulting algorithm has O(log 2 n) time complexity on n-processor PRAM and hypercubic computers and O(k 2 n 1/k ) time complexity on a k-dimensional mesh with n processors. We also analyze the time complexity of the algorithm for m = o(n) and its special case of m = θ(1).

Self-pumped phase-conjugate interferometer with a photorefractive iron-doped lithium-niobate crystal

A single object wave is amplitude divided by a beam splitter into two waves of equal intensity that are made to interfere at the back surface of an iron-doped lithium-niobate crystal so that the normal to the back surface is the angular bisector of the input waves. The interference results in the formation of a phase grating (Bragg grating) in the volume of the crystal. These waves are diffracted at the Bragg grating on both the front focal plane and the back focal plane of the crystal. The wave diffracted in the back focal plane from the Bragg grating and counterpropagating to the incident wave is observed to be the phase conjugate of the input object wave. The wave diffracted in the front focal plane of the Bragg grating is incorporated into the design of an interferometer to measure a specific in-plane displacement of the object wave. It is theoretically evaluated and experimentally demonstrated that interferometers such as those that incorporate conjugate-wave pairs are highly sensitive.