This paper presents the idea of a batch form of the Hough transform, the Compact Hough Transform (CHT), which aims at detecting locations with high probability of belonging to a shape of an approximate size. The CHT is used in a problem of segmentation of cell nuclei, where the nuclear boundary is detected using a method based on maximum likelihood.

This paper presents a new tool based on DSmT overcome the shortcoming of DST[l0][l 1], its precision still (Dezert-Smarandache Theory) and fast-Hough self-localization need to be improved further, since it didn't consider which is applied to autonomous mobile robot's map redistributing the conflicting mass with PCR rule [12] or reconstruction. Uncertainty from sonar information is fused and oth...

We present an approach for automatic bone age classification from hand x-ray images using the Discriminative Generalized Hough Transform (DGHT). To this end, a region, characteristic for the bone age (e.g. an epiphyseal plate), is localized and subsequently classified to determine the corresponding age. Both steps are realized using the DGHT, whereat the difference of the approaches lies within...

In this paper we propose the use of the Randomized Hough Transform algorithm for the determination of the proportions of pure classes present in sets of mixed pixels, for large datasets (for which the deterministic Hough is prohibitively slow) and in the presence of outliers (ie in cases that the classical Least Square Error method cannot cope). We demonstrate our results both with simulated an...

In this work we propose a new method to detect arbitrary planar shapes from a previous template and calculate the parameters that define the transformations between the new image and the template. The image contains a perspective projection of the template subjected to two angles transformation, called tilt and pan, a displacement a rotation and a scaling. The method uncouples parameter calcula...

This paper addresses the localization of anatomical structures in medical images by a Generalized Hough Transform (GHT). As localization is often a pre-requisite for subsequent model-based segmentation, it is important to assess whether or not the GHT was able to locate the desired object. The GHT by its construction does not make this distinction. We present an approach to detect incorrect GHT...

The recognition of shapes in images using Pairwise Geometric Histograms has previously been confined to fixed scale shape. Although the geometric representation used in this algorithm is not scale invariant, the stable behaviour of the similarity metric as shapes are scaled enables the method to be extended to the recognition of shapes over a range of scale. In this paper the necessary addition...

An approach for automatic object localization in medical images utilizing an extended version of the generalized Hough transform (GHT) is presented. In our approach the shape model in the GHT is equipped with specific model point weights, which are used in the voting process. The weights are adjusted in a discriminative training procedure, which aims at a minimal localization error of the GHT. ...