Curved object location by Hough transformations and inversions
Pattern Recognition
Antialiasing the Hough transform
CVGIP: Graphical Models and Image Processing
CVGIP: Image Understanding
Equivalence of Hough curve detection to template matching
Communications of the ACM
Graphics Recognition - from Re-engineering to Retrieval
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
A new shape descriptor defined on the radon transform
Computer Vision and Image Understanding
Recognition of wheat grain quality using log-hough representation and neural networks
Machine Graphics & Vision International Journal
Fast curvilinear structure extraction and delineation using density estimation
Computer Vision and Image Understanding
A new shape descriptor defined on the Radon transform
Computer Vision and Image Understanding
Invariant pattern recognition using the RFM descriptor
Pattern Recognition
DTW for matching radon features: a pattern recognition and retrieval method
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
The generalization of the R-transform for invariant pattern representation
Pattern Recognition
| Hi-index | 0.14 |
A novel image processing technique for the extraction of parameters characteristic of the shape and angularity of abrasive powder particles is proposed. The image data are not analyzed directly. Information concerning angularity and shape is extracted from the parametric transformation of the 2D binarized edge map. The transformation process used, the Radon Transform, is one to many, that is, each image point generates in transform space the parameters of all the possible curves on which it may lie and the resulting distribution is an accumulation of that evidence. Once the image data are segmented, the technique has the potential to deliver a comprehensive numerical description of the shape and angularity of the particles under investigation without the need for further interaction by the operator. The parameters obtained are arranged into a Taxonomy according to their usefulness in categorizing the shapes under inspection. The technique is novel in that it offers an analytical definition of a corner and its apex and it automatically selects only those protrusions coincident with the convex hull of the shape and, hence, those most likely to contribute to the process of abrasion. The advantages and potential pitfalls of using the technique are illustrated and discussed using real image data.