Efficient Fuzzy Set Theoretic Approach to Image Corner Matching

Corner matching in digital images is a key step in several applications in computer vision such as motion estimation, object recognition and localization, 3D reconstruction etc. Accuracy and reliability of corner matching algorithms are two important criteria. In this paper, corner correspondence between two images is established in the presence of intensity variations, inherent noise and motion blur using a fuzzy set theoretic similarity measure. The proposed matching algorithm needs to extract set of corner points as candidates from both the frames. Fuzzy set theoretic similarity measure is used here as fuzzy logic is a powerful tool which is able to deal with ambiguous data. Experimental results conducted with the help of various test images show that the proposed approach is superior compared existing corner matching algorithms (conventional and recent) considered in this paper under non-ideal conditions. DOI: 10.17762/ijritcc2321-8169.15021

Research on robust salient object extraction in image

制度:新 ; 文部省報告番号:甲2641号 ; 学位の種類:博士(工学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新480

Line Based Trinocular Stereo

An approach to solving the stereo correspondence problem in trinocular stereo vision is described. It is based on geometric matching constraints relating the orientation of lines extracted in three images taken from different viewpoints. These novel constraints are termed unary orientation and binary orientation constraints. Matching is achieved within an optimisation framework in which the constraints are encoded into a cost function that is optimised using the simulated annealing method. Results are demonstrated and the characteristics of the approach are explored on both synthetic and real 1 trinocular images.

Structural matching by discrete relaxation

This paper describes a Bayesian framework for performing relational graph matching by discrete relaxation. Our basic aim is to draw on this framework to provide a comparative evaluation of a number of contrasting approaches to relational matching. Broadly speaking there are two main aspects to this study. Firstly we locus on the issue of how relational inexactness may be quantified. We illustrate that several popular relational distance measures can be recovered as specific limiting cases of the Bayesian consistency measure. The second aspect of our comparison concerns the way in which structural inexactness is controlled. We investigate three different realizations ai the matching process which draw on contrasting control models. The main conclusion of our study is that the active process of graph-editing outperforms the alternatives in terms of its ability to effectively control a large population of contaminating clutter

Поиск объектов на изображениях с помощью графов

Данная работа посвящена проблеме поиска объектов на изображении. Для её решения предлагается использовать метод на основе применения графа, описывающего изображение. Данный граф должен обладать тем свойством, что отдельным объектам на изображении должны соответствовать его подграфы. Тогда задача поиска объекта сводится к выделению соответствующего подграфа. Для описания изображения предлагается использовать граф, построенный на основе использования структурных элементов, выделенных с помощью мультимасштабного представления. Данный граф позволяет отражать структуру как текстурированных, так и нетекстурированных объектов. Для выделения подграфов, соответствующих искомым объектам, используются средства, основанные на построении дополнительного графа-пирамиды. Экспериментальная проверка использования данного графа и средств его обработки для поиска текстурированных и слабо текстурированных объектов показала их высокую эффективность. Сравнение с аналогами показало значительное превосходство предложенных средств при поиске слабо текстурированных объектов.Дана робота присвячена проблемі пошуку об’єктів на зображенні. Для її вирішення пропонується використовувати метод на основі вживання графа, що описує зображення. Даний граф повинен володіти тією власти- вістю, що окремим об’єктам на зображенні повинні відповідати його підграфи. Тоді задача пошуку об’єкта зводиться до виділення відповідного підграфа. Для опису зображення пропонується використовувати граф, побудований на основі використання структурних елементів, виділених за допомогою мультимасштабного представлення. Даний граф дозволяє відображати структуру як текстурованих, так і нетекстурованих об’єктів. Для виділення підграфів, відповідних шуканим об’єктам, використовуються засоби, засновані на побудові додаткового графа-піраміди. Експериментальна перевірка використання даного графа і засобів його обробки для пошуку текстурованих і слабо текстурованих об’єктів показала їх високу ефективність. Порівняння з аналогами показало значну перевагу запропонованих засобів при пошуку слабо текстурованих об’єктів.This work is devoted to object search in images. To solve this problem, the method based on the use of a graph that describes the image is applied. The given graph should have such property that the individual objects in the image must comply with its subgraphs. In such case, the task of object search is limited to allocation of corresponding subgraph. To describe the images, it is suggested to use a graph constructed on the basis of the structural elements, which are identified with the help of multi-scale representation. This graph can reflect the structure of both textured and non-textured objects. To separate subgraphs, which correspond to the desired objects, the tools based on the construction of additional graph pyramid are used. Experimental verification of a given graph, and means of processing to search for textured and weakly textured objects demonstrated their high efficiency. Comparison to analogues showed significant superiority of the proposed means at searching poorly textured objects

Disambiguating Multi–Modal Scene Representations Using Perceptual Grouping Constraints

In its early stages, the visual system suffers from a lot of ambiguity and noise that severely limits the performance of early vision algorithms. This article presents feedback mechanisms between early visual processes, such as perceptual grouping, stereopsis and depth reconstruction, that allow the system to reduce this ambiguity and improve early representation of visual information. In the first part, the article proposes a local perceptual grouping algorithm that — in addition to commonly used geometric information — makes use of a novel multi–modal measure between local edge/line features. The grouping information is then used to: 1) disambiguate stereopsis by enforcing that stereo matches preserve groups; and 2) correct the reconstruction error due to the image pixel sampling using a linear interpolation over the groups. The integration of mutual feedback between early vision processes is shown to reduce considerably ambiguity and noise without the need for global constraints

Structural graph matching using the EM algorithm and singular value decomposition

This paper describes an efficient algorithm for inexact graph matching. The method is purely structural, that is, it uses only the edge or connectivity structure of the graph and does not draw on node or edge attributes. We make two contributions: 1) commencing from a probability distribution for matching errors, we show how the problem of graph matching can be posed as maximum-likelihood estimation using the apparatus of the EM algorithm; and 2) we cast the recovery of correspondence matches between the graph nodes in a matrix framework. This allows one to efficiently recover correspondence matches using the singular value decomposition. We experiment with the method on both real-world and synthetic data. Here, we demonstrate that the method offers comparable performance to more computationally demanding method