There have- been many attempts to automate such processes. However, few have yet made the transition from research topic to production method. One reason for this is that scientists seem to be infatuated with anything mathematical.
If something can be expressed as an equation we treat it with profound respect, if it is merely descriptive we tend to be dismissive.
Pure research in computer recognition tasks often pursues theories of shape representation and detection as goals in themselves without any concern being given to their computability or to any application specific adaptations. In addition, the avail- ability and applicability of the results of such research is often hampered by the computer vision community failing to recognize that the potential user may lack some of the basic skills needed in either computing or mathematics.
This book is aimed in particular at two groups of potential users and the problems they may encounter. The first group consists of 'non-mathematical' academics who simply want to use computer vision as a tool in their own research programs. Such people may be, for example, cytologists or biolog- ists whose only need for anything mathematical is a good know- ledge of statistics. The opportunity to relay useful work to these people can be lost if the computer vision community does not adopt a more enlightened perspective on the comprehensibility of what it is producing.
In particular, those of us who routinely use math- ematics in ourwork lose sight of the fact that it is a skill which has to be developed. Some of the more advanced concepts are anything but intuitively obvious, it is only by using them that we are able to understand and manipulate them.
Large sections of the book set out to develop the necessary mathematical skills with unashamedly simple, wholly pictorial explanations. These are aimed at develop- ing a strong intuitive understanding of the underlying mathematics before introducing any complicated notation. Anyone who does not need these sections can simply skip them. Page 5 The second group are those people in industry. It is often difficult for such people tomake use of current research because they lack the background information needed.
This makes it difficult to distin- guish between genuine trends and commercially inconsequential developments in an area of research.
For this reason companies are often reluctant to take on board new advances. Moreover, smaller companies may have to operate within cost constraints which may well be the final arbiters in any decision to implement new technology. Neither prior … Expand. Highly Influenced. View 4 excerpts, cites background. The Dynamic Generalized Hough transform. The Hough Transform is an image processing algorithm which is used to extract geometric primitives from digital images. It has a number of desirable properties, typically robustness to noise and data … Expand.
The dynamic generalized Hough transform: Its relationship to the probabilistic Hough transforms and an application to the concurrent detection of circles and ellipses. An extension to the randomized hough transform exploiting connectivity. Houghtool -- A software package for the use of the Hough transform. The Hough Transform HT is a popular method for detecting curve segments in an image.
A software package, the Houghtool, is proposed to calculate the HT. Several methods for line detection are … Expand. A Hough Transform with projection for velocity estimation. View 1 excerpt, cites methods. Active intelligent vision using the dynamic generalized Hough Transform. Modification of hough transform for circles and ellipses detection using a 2-dimensional array.
Dynamic generalized Hough transform. A new algorithm for the Generalized Hough transform is presented. By making computational recipes and advice available to the non-specialist, the book aims to popularize the technique, and to provide a bridge between low level computer vision tasks and specialist applications.
In addition, Shape Detection in Computer Vision Using the Hough Transform assesses practical and theoretical issues which were previously only available in scientific literature in a way which is easily accessible to the non-specialist user. It is an important textbook which will provide postgraduate students with a thorough grounding in the field, and will also be of interest to junior research staff and program designers. Hough transform Radon transform Shape Detection algorithms computer vision object recognition.
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