A method for the automatic detection of buildings and their roof planes from LIDAR data and multispectral images is presented. For building detection, a classification technique is applied in a hierarchic way to overcome the problems encountered in areas of heterogeneous appearance of buildings. The detection of roof planes is based on a region growing algorithm applied to the LIDAR data, the s...

As the applications of the OCR are widely expanding recently, computers have to extract character patterns from various types of images such as scanned document images, scene images and video frames. Many methods for character pattern extraction have been proposed so far. They were designed and tuned for a special type of image and for a certain input device. However, we have many images which ...

A novel approach for segmentation of grayscale images, which are color scene originally, is proposed. Many algorithms have been elaborated for a grayscale image segmentation. All those approaches have been discussed in a luminance space, because it has been considered that grayscale images do not have any color information. However, a luminance value has color information as a set of correspond...

We propose a method for automatically correcting the spherical topology of any segmentation under any digital connectivity. A multiple region growing process, concurrently acting on the foreground and the background, divides the segmentation into connected components and successive minimum cost decisions guarantee convergence to correct spherical topology. In contrast to existing procedures tha...

Extracting textured objects from natural scenes is a challenging task in computer vision. The main difficulties arise from the intrinsic randomness of natural textures and the high-semblance between the objects and the background. In this paper, we approach the extraction problem with a seeded region-growing framework that purely exploits the statistical properties of intensity inhomogeneity. T...

High performance coding of image sequences requires efficient motion estimation and compensation. Block matching techniques are the usual choice. However they produce irregular motion fields and require subsequent regularization. This paper reports on a motion estimation technique that merges block matching with polynomial approximation and region growing to achieve such a regularization of the...

Vessel diameter is an important factor for indicating retinal microvascular signs. In automated retinal image analysis, the measurement of vascular width is a complicated process as most of the vessels are few pixels wide. In this paper, we propose a new technique to measure the retinal blood vessel diameter which can be used to detect arteriolar narrowing, arteriovenous (AV) nicking, branching...

Prostate segmentation in MRI may be difficult at the interface with the bladder where the contrast is poor. Coupled-models that segment simultaneously both organs with non-overlapping constraints offer a good solution. As a presegmentation of the structures of interest is required, we propose in this paper a fast deformable model to segment the bladder. The combination of inflation and internal...

We present a novel technique for the 3D segmentation of unknown objects from cluttered dual-energy Computed Tomography (CT) data obtained in the baggage security-screening domain. Initial materials-based coarse segmentations, generated using the Dual-Energy Index (DEI), are refined by partitioning at automatically-detected regions. Partitioning is guided by a novel random forest based quality m...

A computer system has been developed for evaluating the morphometrical feature extraction. The features are derived directly from a digital scan of breast fine needle biopsy slides. First the background elimination by thresholding hue component is applied, then the actual segmentation is done with region growing technique. The quality of feature space is measured with classifier based on nonpar...