Eliciting visual primitives for detection of elongated shapes

Abstract This paper deals with the problem of eliciting visual primitives for visual search with the aim of detecting 2D objects characterized, primarily, by an elongated shape. The paper proposes a new visual primitive obtained by combining in a suitable correlation, a basic set of standard local features. This primitive is able to synthesize the information associated with local features and, as a more effective ensemble of proprieties of the considered model, enhance detection. The paper discusses the approach, presents the new primitive and evaluates its robustness in the case of non-ideal and noisy images. Finally an application to the context of visual inspection is presented.

[1]  Anil K. Jain,et al.  BONSAI: 3D object recognition using constrained search , 1990, ICCV.

[2]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[3]  Ruud M. Bolle,et al.  A Complete and Extendable Approach to Visual Recognition , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Virginio Cantoni,et al.  Artificial vision : image description, recognition and communication , 1997 .

[5]  Josef Kittler,et al.  A survey of the hough transform , 1988, Comput. Vis. Graph. Image Process..

[6]  Charles R. Dyer,et al.  Model-based recognition in robot vision , 1986, CSUR.

[7]  A. Treisman.  Search, similarity, and integration of features between and within dimensions. , 1991, Journal of experimental psychology. Human perception and performance.

[8]  Luciano da Fontoura Costa,et al.  Effective Detection of Digital Bar Segments with Hough Transform , 1993, CVGIP Graph. Model. Image Process..

[9]  Frans C. A. Groen,et al.  Discretization errors in the Hough transform , 1981, Pattern Recognit..

[10]  Amy R. Reibman,et al.  Hough transform and signal detection theory performance for images with additive noise , 1990, Comput. Vis. Graph. Image Process..