The fast and highly reliable method reported here uses two techniques to detect all types of defects, such as unsoldered leads, solder bridges, and misalignes leads in the minute solder joints of high density mounted devices. One technique uses external force applied by an air jet that vibrates or shifts unsoldered leads. The vibration and shift is detected as a change in the speckle pattern produced by laser illumination of the solder joints. The other technique uses fluorescence generated by short-wavelength laser illumination. The fluorescence from a printed circuit board produces a silhouette of the solder joint and this image is processed to detect defects. Experimental results show that this inspection method detects all kinds of defects accurately and with a very low false alarm rate.

The authors propose a method of detecting intruders around power line towers using a new image processing technique. With current technology for outdoor imaging, a varitey of factors may lead to erroneous image processing, such as changes of background brightness, rustling of leaves, mist, rain, intrusion of small animals, etc. These problems were solved as follows. With this method, a change of image, which may indicate an intruder, is first detected using a histogram of the brightness difference between a reference image and an observed image. The detected differences are further analyzed to determine whether they represent a human intruder by evaluating a restraint based on the number, the area, the dimensions of the circumscribing rectangle and the center of gravity of the detected portion. Field testing confirmed the method's usefulness, with a successful intruder detection rate of 82%.

This paper describes a new algorithm for finding the contours of a moving object in an image sequence. A distinctive feature of this algorithm is its complete bottom-up strategy from image data to a consistent contour description. In our algorithm, an input image sequence is immediately converted to a complete set of quasi logical spatio-temporal measures on each pixel, which provide constraints on varying brightness. Then, candidate regions in which to localize the contour are bounded based on consistent grouping among neighboring measures. This reduces drastically the ambiguity of contour location. Finally, Some mid-level constraints on spatial and temporal smoothness of moving boundaries are invoked, and they are combined with these low-level measures in the candidate regions. This is performed efficiently by the regularization over the restricted trajectory of the moving boundary in the candidate regions. Since any quantity is dimensionless, the results are not affected by varying conditions of camera and objects. We examine the efficiency of this algorithm through several experiments on real NTSC motion pictures with dynamic background and natulal textures.

This paper proposes a new method for automatic improvement in image quality through adjusting the image sharpness. This method does not need prior knowledge about image blur. To improve image quality, the sharpness must be adjusted to an optimal value. This paper shows a new method to evaluate sharpness without MTF. It is considered that the human visual system judges image sharpness mainly based upon edge area features. Therefore, attention is paid to the high spatial frequency components in the edge area. The value is defined by the average intensity of the high spatial fequency components in the edge area. This is called the image edge sharpness" value. Using several images, edge sharpness values are compared with experimental results for subjective sharpness. According to the experiments, the calculated edge sharpness values show a good linear relation with subjective sharpness. Subjective image sharpness does not have a monotonic relation with subjective image quality. If the edge sharpness value is in a particular range, the image quality is judged to be good. According to the subjective experiments, an optimal edge sharpness value for image quality was obtained. This paper also shows an algorithm to alter an image into one which has another edge sharpness value. By altering the image, which achieves optimal edge sharpness using this algorithm, image sharpness can be optimally adjusted automatically. This new image improving method was applied to several images obtained by scanning photographs. The experimental results were quite good.

As in other fields, the automatization of railway maintenance work is a firm requirement. The authors have developed a system detecting obstacles around a railway for practical railway inspection. The system is based on an original laser-sectioning method and characterized by high accuracy with wide view and in-motion operation. It was confirmed that a static calibration was performed at an accuracy of within 5 mm. Furthermore, a theoretical estimation predicted that dynamic errors can be eliminated within a resolution of 4 mm by means of rail movement detection. In field tests on the Chuo Line, facilities were successfully inspected at speeds up to 40km/h.

This paper proposes a scheme that offers robust extraction of target images in standard view from input facial images, in order to realize accurate and automatic identification of human faces. A standard view for target images is defined using internal facial features, i.e., the two eyes and the mouth, as steady reference points of the human face. Because reliable detection of such facial features is not an easy task in practice, the proposed scheme is characterized by a combination of two steps: first, all possible regions of facial features are extracted using a color image segmentation algorithm, then the target image is selected from among the candidates defined by tentative combination of the three reference points, through applying the classification framework using the sub-space method. Preliminary experiments on the scheme's flexibility based on subjective assessment indicate a stability of nearly 100% in consistent extraction of target images in the standard view, not only for familiar faces but also for unfamiliar faces, when the input face image roughly matches the front view. By combining this scheme for normalizing images into the standard view with an image matching technique for identification, an experimental system for identifying faces among a limited number of subjects was implemented on a commercial engineering workstation. High success rates achieved in the identification of front view face images obtained under uncontrolled conditions have objectively confirmed the potential of the scheme for accurate extraction of target images.

Since its successful launch in February of 1992, the Japan Earth Resources Satellite-1 (JERS-1) has been sending back high resolution images of the earth for various studies, including the investigation of earth resources, the preservation of environments and the observation of coastal lines. Currently, received images are processed using the Earth Resources Satellite Data Information System (ERSDIS). The ERSDIS is a high speed image processing system utilizing an extended cellular array processor as its main processing module. The extended cellular array processor (CAP), consisting of 4096 processing elements configured into a two-dimensional array, is designed to have many parallel processing optimizing capabilities targetting large-scale image processing at a high speed. This paper desctribes a typical image processing flow, the structure of the ERSDIS, and the details of the CAP design.

The character binarization method MTC is developed for enhancing the recognition of characters in general outdoor images. Such recognition is traditionally difficult because of the influence of illumination changes, especially strong shadow, and also changes in character, such as apparent character sizes. One way to overcome such difficulties is to restrict objects to be processed by using strong hypotheses, such as type of object, object orientation and distance. Several systems for automatic license plate reading are being developed using such strong hypotheses. However. their strong assumptions limit their applications and complicate the extension of the systems. The MTC method assumes the most reasonable hypotheses possible for characters: they occupy plane areas, consist of narrow lines, and external shadow is considerably larger than character lines. The first step is to eliminate the effect of local brightness changes by enhancing feature including characters. This is achieved by applying mathematical morphology by using a logarithmic function. The enhanced gray-scale image is then binarized. Accurate binarization is achieved because local thresholds are determined from the edges detected in the image. The MTC method yields stable binary results under illumination changes, and, consequently, ensures high character reading rates. This is confirmed with a large number of images collected under a wide variety of weather conditions. It is also shown experimentally that MTC permits stable recognition rate even if the characters vary in size.

Recently, a flexible image database retrieval system where image keywords can be captured automatically is strongly required, in order to manage a practical number of image data successfully. However, image recognition/understanding technology level is not generally sufficient enough to achieve this requirement. In order to overcome this problem, a new type of image database framework is proposed in this paper. In the proposed system, image keywords are extracted in fully-automated fashion by the flexible and generalized image recognition system. Image keywords employed in this system are a collection of recognized objects in the image, where achieved recognition levels are allowed to be intermediate or imperfect. The concept of recognition thesaurus" has been introduced to manage these various abstraction level of kerwords successfully. As an embodiment of this concept, an experimental image database with various types of sports scenes has been implemented and various retrieval evaluations have been performed. Experimental results reveal the effectiveness of the proposed method.

We are concerned with a subclass of deterministic pushdown automata (dpda) called very simple dpda's, and present a new direct branching algorithm for checking the inclusion for a pair of languages accepted by these dpda's. As usual, we take the maximal thickness (i.e., the length of the shortest input strings that make each stack symbol go to empry) of all stack symbols into account as one parameter of the given dpda's. Then the worst-case time complexity of our algorithm is polynomial with respect to these parameters. Without considering the thickness, the complexity is single exponential in the description length of the given dpda's. As far as we are concerned with very simple dpda's, our algorithm is very simple and direct, and is faster and much better than the previously given algorithms for the inclusion problem of dpda's.

String grammars (languages) have been extensively studied from 60's. On the other hand, the transformational grammar, proposed by Chomsky, contains the transformation from the set of derivation trees of context-free language to the surface set. And the grammar regarded a tree as an input sentence to some transducer. After that from latter half of 60's, the studies of acceptor, transducer, and so on, whose input is a tree, have been done extensively. In this paper we propose, as a model, a new type of transducer which translates trees into trees and investigate its fundamental properties. The model proposed here is the pushdown tree transducer (for shortly PDTT) that is an extension of the finite state tree transducer discussed by J. W. Thacher, W. C. Rounds, J. Engelfriet, and so on. The main subjects discussed here (we consider only top-down case (t-PDTT)), are as follows: (1) final state t-PDTT translation is equivalent to empty stack t-PDTT translation and vice versa, (2) for any t-PDTT, a single state t-PDTT which is equivalent to it always exists, (3) as a standard form the symmetric stack form t-PDTT is proposed and based on this, it is shown that any single state t-PDTT can be always converted into a linear stack t-PDTT, and so on.

As RAMs become dense, their reliability reduces because of complex interactions between memory cells and soft errors due to alpha particle radiations. In order to rectify this problem, RAM manufacturers have started incorporating on-chip (built-in) ECC. In order to minimize the area overhead of on-chip ECC, the same technology is used for implementing the check bits and the information bits. Thus the check bits are exposed to the same failure modes as the information bits. Furthermore, faults in the check bits will manifest as uncorrectable multiple errors when a soft error occurs. Therefore it is important to test the check bits for all failure modes expected of other cells. In this paper, we formulate the problem of testing RAMs with on-chip ECC capability. We than derive necessary and sufficient conditions for testing the check bits for arbitrary and adjacent neighborhood pattern sensitive faults. We also provide an efficient solution to test a memory array of N bits (including check bits) for 5-cell neighborhood pattern sensitive faults in O (N) reads and writes, with the check bits also tested for the same fault classes as the information bits.

A method for detecting multiple rigid motions in images from an optical flow field obtained with multi-scale, multi-orientation filters is proposed. Convolving consecutive gray scale images with a set of eight orientation-selective spatial Gaussian filters yields eight gradient constraint equations for the two components of a flow vector at every location. The flow vector and an uncertainty measure are obtained from these equations. In the neighborhood of motion boundary, the uncertainty of the flow vectors increase. By using multiple sets of filters of different scales, multiple flow vectors are obtained at every location, from which the one with minimal uncertainty measure is selected. The obtained flow field is then segmented in order to solve the aperture problem and to remove noise without blurring discontinuity in the flow field. Discontinuities are first detected as those locations where flow vectors have relatively larger uncertainty measures. Then similar flow vectors are gouped into regions. By modeling flow vectors, regions are merged to form segments each of which belongs to a planar patch of a rigid object in the scene.

This paper describes a noise resistant algorithm for recovering the three-dimensional motion of a rigid object from optical flow. First, it is shown that in the absence of noise three-demensional motion can be obtained exactly by a linear algorithm except in the special case in which the surface of the object is on a general quadratic surface passing through the viewpoint, and the normal vector of the surface at the viewpoint is perpendicular to the translation velocity vector. In the presence of noise, an evaluation function is introduced based on the least squares method. It is shown, however, that the solution which minimizes the evaluation function is not always optimal due to statistical bias. To deal with this problem, a method to eliminate the statistical bias in the evaluation function is proposed for zero mean white noise. Once the statistical bias is eliminated, the solution of the linear algorithm coincides with the correct solution by means of expectation. In this linear algorithm, only the eigenvector corresponding to the zero eigenvalue of a 33 matrix is necessary to find the translational velocity. Once the translational velocity is obtained, the rotational velocity can be computed directly. This method is also shown to be noise resistant by computer simulation.

Knowledge-based Database Assistant is an expert system designed to help novice users formulate correct and complete database queries. This paper describes a knowledge-based database assistant with advanced facilities such as (1) a menu-based querymaking guidance, (2) a menu-based natural-language user-interface, and (3) database-commands generator which formulates formal database queries with SQL language. The system works as an intelligent front-end to an SQL database system or a computer-aided SQL tutorial-system. In this paper, we also discuss a semantic-network model, named S-Net, which is used to represent the knowledge for formal database-query formulating processes. The menu-based English user-interface allows end-users to make a query by filling a certain query pattern with appropriate words. The query-pattern filling process is guided by pop-up menus provided by the system. The query-pattern instances thus obtained are then translated into formal database queries. The translation is carried out by evaluating operations on S-Net knowledge-base which conveys knowledge about application domain, and the underlying database schema.

To derive blood flow dynamics from cineangiograms (CAG), we have developed an image processing algorithm to estimate a two-dimensional blood fiow velocity map projected on CAG. Each image area of CAG is diveded into blocks, and it is assumed that the movement of the contrast medium between two serial frames is restricted only to adjacent blocks. By this assumption, a fundamental equation" and the maximum flow constraints" are derived. The equation and constraints state the relationship between the volume of contrast medium in each block and the flow components" that are the volumes of contrast medium flowing from/to its adjacent blocks. The initial guess" that is a set of approximately obtained flow components is corrected using these relationships. The corrected flow components are then transformed into blood flow velocities, which are illustrated in the form of a needle diagram. In numerical experiments, the estimation error between the real flow velocity generated artificially and the flow velocity estimated with our algorithm was evaluated under one of the worst conditions. Although the maximum error was fairly large, the estimated flow velocity map was still acceptable for visual inspection of flow velocity pattern. We then applied our algorithm to an abdominal CAG (clinical data). The results showed flow stagnation and reverse flow in the abdominal aneurysm, which are consistent with the presence of a thrombus in the aneurysm. This algorithm may be a useful diagnostic tool in the assessment of vascular disease.

There have been several studies related to a reduction of the amount of computational resources used by Turing machines. As consequences, linear speed-up theorem" tape compression theorem", and reversal reduction theorem" have been obtained. In this paper, we consider reversal- and leaf-bounded alternating Turing machines, and then show that the number of leaves can be reduced by a constant factor without increasing the number of reversals. Thus our results say that a constant factor on the leaf complexity does not affect the power of reversal- and leaf-bounded alternating Turing machines

For each two positive integers r, s, let [1DCM(r)-Time(n^s)] ([1NCM(r)-Time(n^s)]) and [1DCM(r)-Space(n^s)] ([1NCM(r)-Space(n^s)]) be the classes of languages accepted in time n^s and in space n^s, respectively, by one-way deterministic (nondeterministic) r-counter machines. We show that for each X{D, N}, [1XCM(r)-Time(n^s)][1XCM(r+1)-Time(n^s)] and [1XCM(r)-Space(n^s)][1XCM(r+1)-Space(n^s)]. We also investigate the relationships between one-way multicounter machines and cooperating systems of one-way finite automata. In particular, it is shown that one-way (one-) counter machines and cooperating systems of two one-way finite automata are equivalent in accepting power.