A new technique, named DPOL MUM, is proposed for the segmentation of multi-frequency polarimetric SAR images. By following a Maximum Likelihood approach, an optimal split-merge test is derived, which fully exploits the characteristic block-diagonal structure of the data covariance matrix. This test is demonstrated to yield a reduced fluctuation error than the extension of the polarimetric test ...

We propose a novel approach for the detection of temporally impulsive dirt impairments in archived film sequences. Our method does not require motion compensation and uses raw differences between the current frame and each of the previous and next frames to extract a confidence signal which is used to localize and label dirt regions. A key feature of our method is the removal of false alarms by...

Preprocessing of character images is an important step in recognition. We describe a method of enhancing binary character images to assist the subsequent recognition process in both handwritten and machine-printed documents. The method performs selective and adaptive stroke "filling" with a neighborhood operator which emphasizes stroke connectivity. An improvement of 7% points was realized in r...

This work presents a segmentation method based on a region growing approach. It has been implemented in the geographic information and image processing system (SPRING) which has been developed at INPE. The technique is applied to segment images which are being used to assess land use changes in the Amazon region. Segmented Landsat-TM images are shown to illustrate the technique.

A new model for representing an unorganised 3D data points set is proposed. Based on superquadrics, this model allows to describe the points set with a union of superellipsoids. Two different segmentation and modeling methods are developed in order to determine the whole model: a region growing approach and a split and merge one. This second method leads to a low sensitive model compared to the...

Proposed in this paper is an efficient algorithm to remove self-intersections from the raw offset triangular mesh. The resulting regular mesh can be used in shape inflation, tool path generation, and process planning to name a few. Objective is to find the valid region set of triangles defining the outer boundary of the offset volume from the raw offset triangular mesh. Starting with a seed tri...

A new region growing method for finding the boundaries of blobs is presented. A unique feature of the method is that at each step, at most one pixel exhibits the required properties to join the region. The method uses two novel discontinuity measures, average contrast and peripheral contrast, to control the growing process.

Region growing and edge detection are two popular and common techniques used for image segmentation. Region growing is preferred over edge detection methods because it is more robust against low contrast problems and effectively addresses the connectivity issues faced by edge detectors. Edgebased techniques, on the other hand, can significantly reduce useless information while preserving the im...

In the context of an experimental virtual-reality surgical planning software platform, we propose a fully self-assessed adaptive region growing segmentation algorithm. Our method successfully delineates main tissues relevant to head and neck reconstructive surgery, such as skin, fat, muscle/organs, and bone. We rely on a standardized and selfassessed region-based approach to deal with a great v...

Multi-resolution and region-growing strategies have been successfully used in several fields of image processing. In this paper we investigate how these two strategies can be applied for binary tomography. We included these strategies into a reconstruction method using simulated annealing and tested these new methods on different images.