Showing papers on "Object detection published in 1985"

Adaptive Optical Target Detection Using Correlated Images

Abstract: A method for target detection that achieves clutter rejection by the use of multiple observations of the same target scene is developed. Multiple scene observations can be obtained by processing separate frequency bands of the same target scene or by recursively processing sequential observations in time. Optimal detection algorithms are developed, based on the assumption that the image intensity can be modeled as a variable mean spatial Gaussian process. Several fast detection algorithms are derived which make use of the fact that the covariance matrices of many optical and infrared (IR) images can be accurately approximated by diagonal matrices. These algorithms provide efficient solutions to the problem of processing multiple correlated scenes or multiple sequential imaging. Computer simulations based on actual optical and IR image data were used for checking the theoretical results. The new detection algorithms achieved performance improvement in detection signal-to-noise ratio of up to 10 dB over conventional target correlation methods.

A study of the clash detection problem in robotics

Abstract: To solve the clash detection problem we must decide whether a collision will occur between any pair of objects from a set of objects with known shapes and motions. We have considered three methods for performing clash detection: in the first we sample the motion at a finite number of times and perform interference detection at each time; in the second we create models of the shapes and their motions in space-time, and look for intersections between these four-dimensional entities; and in the third we create models of the volumes swept out by the objects. This paper is a brief, comparative study of these three methods, and includes some details of our experiments with the first two methods as implemented in a geometric modelling system.

Automated digital visual inspection with dark-field microscopy

Abstract: In this paper we deal with the problem of detecting and segmenting objects in textured dark-field digital imagery for automated visual-inspection applications. We first present a technique for correcting optical shading effects in conventional dark-field microscopy. After compensating for possible imperfections in the optical setting we address the problem of segmenting objects (defects) in textured dark-field images. The technique that we will follow is based on a sequential application of local operators, which serves the purpose of clustering the object and the background gray levels. This procedure can be considered an extension of average-thresholding-type techniques. Both algorithms for shading correction and object segmentation have fast implementations in general-purpose image-processing pipeline architectures, and therefore they are appealing to real-time computer vision applications. Computational examples showing the appropriateness of the shading-correction procedure as well as the effectiveness of the segmentation wil be discussed.

Identification Of Unique Objects In High Resolution Aerial Images

Abstract: Accurate and reliable detection of unique objects is an important component of an image understanding system. The objects are considered to have a unique pattern and should be recognized based upon their own characteristics. An object detection approach applicable to high resolution aerial images is developed in the paper. The methodologies incorporate features such as minimal sensitivity to the backgrounds on which objects may appear, ability to detect objects appearing in arbitrary orientations, and use of a unified set of operators to analyze various levels of details. Specifically, the gray-level co-occurrence matrix is used to provide the early vision operators. Results of several experiments show promise for the proposed methods. The methods can constitute an important part of an object identification system in which use of such properties as object size, shape, reflectance, etc., is possible.

Three-dimensional vision techniques for an advanced robot system

Abstract: This paper describes 3D vision techniques for an advanced robot system in terms of efficient hardware and practical software. Arm-controlled stereo cameras have been developed for efficient 3D sensing, whose interocular distance, yaw and tilt are under program control. Stereo vision programs are implemented with the aid of the stereo cameras and a high-speed vision processor. Knowledge-guided vision algorithms are realized in a high-level processor, where a priori knowledge regarding the environments, objects and procedure controls are utilized.

FODS - A system for faint object detection and classification in astronomy

Abstract: Structure du systeme FODS pour la detection et la classification des objets faibles developpe au pole ASTRONET de l'observatoire de Trieste. La principale caracteristique du systeme est sa flexibilite. On detaille les operations fondamentales: numerisation de plaque, detection de l'objet, analyse des particularites, calcul parametrique et classification de l'objet

A New Approach to Target Detection and Estimation in Clutter

Abstract: We describe an approach for target detection/state estimation that views the problem as one of a finite state search This approach allows for a natural way to associate measurements and also for dealing with data from heterogeneous sources We describe our model and a scoring function based on the model A search algorithm for target detection and target state estimation is presented, followed by an example

Efficient new techniques for identification and 3D attitude determination of space objects from a single image

Abstract: We present new algorithms for rapid identification and three-dimensional (3D) attitude determination of a solid object from a single image, using a model matching approach. Our scheme allows the observed object to be partially occluded. The object, as well as the model to which it is matched are represented by the 3D surface constituting their boundaries. We assume that these surfaces consist of flat faces, i.e. the object and the model are (not necessarily convex) polyhedra. We represent each by an attributed graph. The nodes of the graph denote faces on the surface and edges indicate the adjacency of faces. Attributes on the nodes are features invariant to 3D motion made up of 2D moment invariants. With this representation the recognition problem becomes a subgraph matching problem between the image of the observed object and the stored models. We present an algorithm for the matching process, furthermore the exact attitude is obtained as a byproduct of the matching procedure.

Object detection apparatus

Abstract: PURPOSE:To attain the automation and labor saving in the detection of an object, by connecting a control apparatus for outputting a scanning angle signal corresponding to the movement of the object to the drive motor connected to the sensor of a distance measuring apparatus using a medium such as an ultrasonic wave. CONSTITUTION:In a usual state wherein an obstacle is absent, a scanning signal is sent to a sensor from a control apparatus and a motor driving circuit operates a front monitoring mode on the basis of this signal and an ultrasonic wave receiver reciprocally moves in a definite range. When the obstacle is detected, the motor driving circuit operates in a tracking mode by a control signal so that a transmitter receiver tracks an object. By this mechanism, not only the automation and labor saving in the detection of the object are enabled but also the detection of the obstacle in a moving body is also effectively performed and both detection operations can be made simple and inexpensive.

Rear object detection device for car

Abstract: PURPOSE:To alarm and display the existence of a rear object when a car is driven in reverse gear by providing a detection sensor of the rear object, alarm display of the existence of the object, damping status detection means and so on. CONSTITUTION:When transmission is selected in a rear position and the power switch of a control circuit 4 is closed, initialization is performed and ports P1 and P4 are set to logic 0. A flip-flop is reset and the timer of a microcomputer 41 is zero-cleared and time is set to t=0. Then the port P1 between t=0 and t= T1 is set to logic 1 and a transmitter 1a sends and issues ultrasonic waves 5a is excited by the oscillation frequency of an oscillator circuit 42 and then wits for time when the time T2 corresponding to the detection length against the preset rear object 6 is reached. Furthermore, if reflected waves 5b are received by the time t=T2 after the ultrasonic waves 5a are issued, the object is assumed to exist in this preset length and a preset alarm tone sounds from a speaker 2.

Invariance in moving target detection

Abstract: Some schemes for detecting moving point targets against structured backgrounds from observations on the output of an imaging system are investigated. When the velocity of the target and the background image are considered as known, it is shown that the uniformly most powerful detector, invariant with respect to image intensity variations, consists of specific spatial-temporal differencing schemes. This places such schemes on a rigorous foundation.

Detection of moving point objects against a moving background.

Abstract: The temporal spectral characteristics of a dim moving point object and a moving background, as observed by a sensor array, are analyzed. This type of problem occurs in remote sensing, machine vision, and many other applications. The diffraction limitation of the sensor optics ensures that the temporal spectrum of the background moving with a finite velocity has a finite maximum bandwidth, regardless of background structure. Because the outputs of the sensor array are time sampled, its spectrum is infinitely replicated over an interval of temporal frequency equal to the reciprocal of the sampling time. If this interval is at least twice as large as the maximum background temporal frequency, there is a region with no background components in the middle of each interval. However, because the point object temporal spectrum in the sampled sensor array output is continuously distributed, this region will contain part of the point object signal. Thus, a criterion for the existence of an effective background suppression filter is that the point object fundamental frequency must be greater than the maximum background temporal frequency. When this criterion is satisfied, the amount of background leakage in the filter depends on the sharpness of its passband response and its stopband characteristics. In general, higher-order filters have sharper response and hence better performance. If the criterion is not met, all types of filter lose their effectiveness since the background signal will leak through the passband of the filter. The fundamental concepts developed here were examined for some typical parameter values. It is shown that for this system the point object can be effectively discriminated. In some cases the point object and background temporal spectral responses vary significantly with spatial position within the field of view. Because the filter's center frequency must match the point object temporal fundamental frequency, it is necessary to use an adaptive filter in these situations.

Knowledge based object detection

Abstract: This paper presents an attempt to combine statistical processing with symbolic processing for the detection of anomalous regions in images with noisy background. Symbolic inferences are used to provide expectations about the image to allow optimisation of statistical routines under these conditions. The approach employs a model of the image formation process and data about the domain.

Fast object segmentation in textured backgrouds

Abstract: In this paper, we deal with the problem of detecting and segmenting objects in textured darkfield digital imagery for automated visual inspection applications. The technique we will follow is based on a sequential application of local operators which serves the purpose of clustering the object and the background gray levels. This procedure can be considered as an extension of average-thresholding type techniques. This algorithm has fast implementations in general purpose image processing pipeline architectures and therefore, it is appealing to real-time computer vision applications. Computational examples showing the effectiveness of the segmentation technique will be discussed.

Astronomical Input to Image Processing Astronomical Output from Image Processing

Abstract: This paper discusses some aspects of image processing — first with a high level look at image processing, its inputs, outputs and operations. Then, a specific research project is examined to illustrate how various image processing functions are used to derive results from image data. The project is the construction of a catalog of galaxies from photographic plates. The functions illustrated include correcting for the nonlinear plate response, modelling and removing the background with a polynomial, removing bright objects, histograms, smoothing, object detection, object parameter estimation, and manipulation of tabular data.

Faint Objects in Crowded Fields: Discrimination and Counting

Abstract: The analysis and classification of faint objects measured on photographic plates (Malagnini et al.,1984) involve a number of problems, which are particularly relevant in the case of crowded regions. The density of the object images can be evaluated by comparing the distribution of the object dimensions with the distribution of the distances between any object and its nearest neighbor. We refer to the case in which the modes of the two distributions are comparable, thus asking for particular caution in the automatic analysis of individual objects. The aspects we will discuss refer to: i) local background estimates and automatic detection, ii) preliminary screening and constraints on the image characteristics and on environment relationships to pass the object to the classifier. The examples given here refer to photographic material processed at the ASTRONET center of Trieste, Osservatorio Astronomico, and fully referenced in the papers by Malagnini et al. (1984) and Santin (1984).