Qualitative features and the generalized hough transform

نویسندگان

  • Suchendra M. Bhandarkar
  • Minsoo Suk
چکیده

-In this paper we show how the use of qualitative features can enhance the performance of recognition and localization techniques, in particular, the Generalized Hough Transform. Qualitative features (i.e. scene features with qualitative attributes assigned to them) are shown to be effective in pruning the search space of possible scene interpretations and also reducing the number of spurious interpretations explored by the recognition and localization technique. The redundancy of the computed transform and the probability of spurious peaks of signilicant magnitude due to random accumulation of evidence are two criteria by which the performance of the Generalized Hough Transform is judged. The straightforward Generalized Hough Transform shows a high probability of spurious peaks of significant magnitude even for small values of redundancy and small magnitude of the search space of scene interpretations. The use of qualitative features enables us to come up with a weighted Generalized Hough Transform where each match of a scene feature with a model feature is assigned a weight based on the qualitative attributes assigned to the scene feature. These weights could be looked upon as membership function values for the fuzzy sets defined by these qualitative attributes. Analytic expressions for the probability of accumulation of random events within a bucket are derived for the weighted Generalized Hough Transform and compared with the corresponding expression for the straightforward Generalized Hough Transform. The weighted Generalized Hough Transform is shown to perform better than the straightforward Generalized Hough Transform. An experiment for the recognition of polyhedral objects from range images is described using dihedral junctions as features for matching and pose computation. The experimental results bring out the advantages of the weighted Generalized Hough Transform over the straightforward Generalized Hough Transform. Object recognition Generalized Hough Transform Qualitative reasoning Fuzzy reasoning

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Fuzzy Probabilistic Model for the Generalized Hough Transform

AbstructA fuzzy-probabilistic model of the Generalized Hough Transform (GHT) based on qualitative labeling of scene features is presented. Qualitative labeling of scene features is shown to be effective in pruning the search space of possible scene interpretations and also reducing the number of spurious interpretations explored by the GHT. Qualitative labeling of scene features is shown to res...

متن کامل

Iris localization by means of adaptive thresholding and Circular Hough Transform

In this paper, a new iris localization method for mobile devices is presented. Our system uses both intensity and saturation threshold on the captured eye images to determine iris boundary and sclera area, respectively. Estimated iris boundary pixels which have been placed outside the sclera will be removed. The remaining pixels are mainly the boundary of iris inside the sclera. Then, circular ...

متن کامل

Image matching under generalized hough transform

The paper analyzes the techniques of image template matching, and gives a matching framework based on generalized Hough transform, which is applicable to lots of current methods. With the framework’s guidance, extracting image features with specific characteristics and devising feature matching algorithms become easier and more efficient. We propose a new fast matching algorithm as evidence. It...

متن کامل

A Hierarchical Hough Transform for Fingerprint Matching

This paper addresses the improvement on the generalized Hough transform for the biometric identification applications. The errors in generalized Hough transform for fingerprint matching are investigated and a new hierarchical Hough transform algorithm is proposed, which is faster and more accurate compared to conventional generalized Hough transform.

متن کامل

Randomized generalized Hough transform for 2-D gray scale object detection

This paper proposes a new algorithm for 2-D object detection called Randomized Generalized Hough Transform (RGHT). It combines the Generalized Hough Transform (GHT) with the Randomized Hough Transform (RHT). Our algorithm can detect arbitrary objects of various scales and orientations in graylevel images. We also demonstrate RGHT’s advantage of high speed, low storage requirement, high accuracy...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Pattern Recognition

دوره 25  شماره 

صفحات  -

تاریخ انتشار 1992