Recognition of partially occluded threat objects using the annealed Hopefield network

Recognition of partially occluded objects has been an important issue to airport security because occlusion causes significant problems in identifying and locating objects during baggage inspection. The neural network approach is suitable for the problems in the sense that the inherent parallelism of neural networks pursues many hypotheses in parallel resulting in high computation rates. Moreover, they provide a greater degree of robustness or fault tolerance than conventional computers. The annealed Hopfield network which is derived from the mean field annealing (MFA) has been developed to find global solutions of a nonlinear system. In the study, it has been proven that the system temperature of MFA is equivalent to the gain of the sigmoid function of a Hopfield network. In our early work, we developed the hybrid Hopfield network (HHN) for fast and reliable matching. However, HHN doesn't guarantee global solutions and yields false matching under heavily occluded conditions because HHN is dependent on initial states by its nature. In this paper, we present the annealed Hopfield network (AHN) for occluded object matching problems. In AHN, the mean field theory is applied to the hybird Hopfield network in order to improve computational complexity of the annealed Hopfield network and provide reliable matching under heavily occluded conditions. AHN is slower than HHN. However, AHN provides near global solutions without initial restrictions and provides less false matching than HHN. In conclusion, a new algorithm based upon a neural network approach was developed to demonstrate the feasibility of the automated inspection of threat objects from x-ray images. The robustness of the algorithm is proved by identifying occluded target objects with large tolerance of their features

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture

The contour tree image encoding technique and file format

The process of contourization is presented which converts a raster image into a discrete set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimises noticeable artifacts in the simplified image. The contour merging technique offers a complementary lossy compression system to the QDCT (Quantised Discrete Cosine Transform). The artifacts introduced by the two methods are very different; QDCT produces a general blurring and adds extra highlights in the form of overshoots, whereas contour merging sharpens edges, reduces highlights and introduces a degree of false contouring. A format based on the contourization technique which caters for most image types is defined, called the contour tree image format. Image operations directly on this compressed format have been studied which for certain manipulations can offer significant operational speed increases over using a standard raster image format. A couple of examples of operations specific to the contour tree format are presented showing some of the features of the new format.Science and Engineering Research Counci

Automatic recognition and inspection of two-dimensional manufactured components

This thesis presents new developments in the field of recognition and inspection of 2D manufactured components. It discusses the problem of recognition and inspection of such components, which may be either flawed or partially completed. Several new methods are proposed that are designed to be used in the solution of this problem. These methods may be divided into two categories. The first involves the component of interest being processed via a suitable feature extraction scheme. This scheme makes measurements of local geometric features of the component which are, by nature, invariant of the component’s position, orientation and scale. These features are known as local features of the component, because they are calculated for only a portion of the area or outline of the entire component. Global features, which are extracted from the whole outline, are not immediately useful because the contribution of acceptable or unacceptable variations, spurious additions and omissions are all arbitrarily combined together, that is, smoothed over. An algorithm is then used to compare the features extracted from the component with the same type of features extracted from its reference component. Each individual geometric entity of the component may be identified after using this process. The second category concerns itself with the replacement of measured point data, derived from the outline of the component, with substitute geometric entities, such as straight lines and circular arcs. This replacement is necessary because measured point data does not describe a manufactured component in the same way as that of the design specification. Only when such a substitution takes place can a spatial comparison between corresponding individual entities be performed, based on the design specifications. In addition, the relationship between the most widely used invariant moments, and Fourier descriptors, is investigated. Fourier Analysis is often used in image processing and Fourier descriptors are often readily available so, for this reason, it is useful to compute invariant moments by using Fourier descriptors. This thesis is organized as follows: Chapter 1 outlines previous research in this field, the need for current research, and the scope of this work. Chapter 2 is devoted to the new subpolygon method. This method is developed for recognition and inspection of relatively simple manufactured components. Chapter 3 proposes the new line-moment method of feature extraction, which is designed for the more complex manufactured components which may be less conveniently examined by the using the subpolygon method. The simplicity and effectiveness, as well as the applications, of line moments are also demonstrated. In addition, the algorithm designed for matching this type of feature with geometric entities is described. Chapter 4 briefly reviews the method of extracting a component’s global features by applying a Fourier Analysis. Since Fourier descriptors and moment invariants are two important types of extracted invariant features, the major concern of this chapter is the development of a mathematical relationship between the two. Several examples involving the use of this method are included later in the chapter. Chapter 5 proposes a novel algorithm for generating substitute geometries, such as lines and arcs, from measured sample point data, such as digitises or pixels. It enables a final comparison between the geometries of a component based on its design specifications. Errors due to the substitution are then minimised. and the deviations between the substitute geometry and the measured sample points may then be calculated. Chapter 6 concludes the thesis and recommends possible further research

Recognition of Occluded Object Using Wavelets

Ph.DDOCTOR OF PHILOSOPH

大脳視覚情報処理に基づく神経振動と曲率表現を用いた物体認識のモデル化に関する研究

Tohoku University佐藤茂雄課