Franklin César Flores

Automatic shadow segmentation in aerial color images

A robust and efficient technique to segment shaded areas in aerial color images is presented here. This technique is based on the physical phenomenon of atmospheric dispersion of the sunlight most well known as the Rayleigh scattering effect. This technique does not depend on special algorithms to classify or to form clusters of objects appearing in complex aerial images. In fact, the mathematical model, derived from the physical model is very simple but it produces consistent results and can be applied to color images obtained by airborne and orbital sensors (e.g., Landsat TM and IKONOS).

New Tensorial Representation of Color Images: Tensorial Morphological Gradient Applied to Color Image Segmentation

This paper proposes a new Tensorial Representation of HSI color images, where each pixel is a 2 times 2 second order tensor, that can be represented by an ellipse. A proposed tensorial morphological gradient (TMG) is defined as the maximum dissimilarity over the neighborhood determined by a structuring element, and is used in the watershed segmentation framework. Many tensor dissimilarity functions are tested and other color gradients are compared. The comparison uses a new methodology for qualitative evaluation of color image segmentation by watershed, where the watershed lines of the n most significant regions are overlaid on the original image for visual comparison. Experiments show that the TMG using Frobenius norm dissimilarity function presents superior segmentation results, in comparison to other tested gradients.

Watershed from propagated markers: An interactive method to morphological object segmentation in image sequences

In this paper, it is introduced an interactive method to object segmentation in image sequences, by combining classical morphological segmentation with motion estimation - the watershed from propagated markers. In this method, the objects are segmented interactively in the first frame and the mask generated by its segmentation provides the markers that will be used to track and segment the object in the next frame. Besides the interactivity, the proposed method has the following important characteristics: generality, rapid response and progressive manual edition. This paper also introduces a new benchmark to do quantitative evaluation of assisted object segmentation methods applied to image sequences. The evaluation is done according to several criteria such as the robustness of segmentation and the easiness to segment the objects through the sequence.

Color Image Gradients For Morphological Segmentation

This paper proposes an approach for color segmentation which is an alternative to the search of a total order in the color space. Instead of looking for a total order, we look for a suitable metric that defines a color gradient, which is a fundamental step of the morphological segmentation paradigm.

A tensorial framework for color images

This paper proposes a new tensorial color representation, obtained by making a correspondence between color models (HSL, IHSL, HSV, RGB and CIELUV) and tensors. Based on this representation, a proposed tensorial morphological gradient (TMG), defined as the maximum dissimilarity over the neighborhood, was tested using several tensor similarity measures. Experimental results illustrate which color models are more suitable to the proposed tensorial representation and which measures give best results in the TMG computation. The watershed transform was used to demonstrate that the proposed representation and the TMG can be applied to segment color images. A quantitative analysis of segmentation results was also conducted.

Automatic design of morphological operators for motion segmentation

A problem of interest in digital video editing is the elimination of moving objects from one video and the introduction of pieces of other videos in their places. A fundamental problem to build computational tools for this purpose is the segmentation of moving objects. The paper approaches this problem with a novel technique based on Beucher-Meyers paradigm (F. Meyer and S. Beucher, 1990), with markers detected by morphological operators designed by computational learning techniques. The objects in the first frames of the video are marked manually and used to train the marker detector. Then, the operator designed is used to mark the objects in the other frames and the paradigm is applied to all frames marked by the detector. Some synthetic and real world examples illustrate the application of the technique proposed. Complex situations such as occlusion are examined.

Morphological operators for segmentation of color sequences

This paper presents a technique for the segmentation of moving objects in color image sequences. The technique is based on Beucher-Meyer paradigm, with markers detected by a morphological operator designed by computational learning (or, equivalently, statistical optimization). Objects in some frames of the video are marked manually and used to train the markers detector. Then, the operator designed is used to mark the objects in the other frames and the paradigm is applied to all frames marked by the detector. Two real world examples illustrate the application of the proposed technique.

Classification of microstructures by morphological analysis and estimation of the hydration degree of cement paste in concrete

Cement is an essential material for the development of the civil construction. The analysis of cement-based materials is useful in the evaluation of mechanical properties, water absorption, air permeability and evolution of hydration degree. The latter is the motivation of this paper. New advantageous techniques of analysis based on the image information are possible using electronic microscopy. We propose here an alternative procedure to the segmentation of microstructures of cement and aggregates in concrete. The central idea consists of a particular use of the morphological operator watershed. We report the results of the analysis of about 450 scanning electron microscope (SEM) images.

The weighted gradient: a color image gradient applied to morphological segmentation

This paper proposes a method for color gradient computation applied to morphological segmentation of color images. The weighted gradient (with weights estimated automatically), proposed in this paper, applied in conjunction with the watershed from markers technique, provides excelent segmentation results, according to a subjective visual criterion. The weighted gradient is computed by linear combination of the gradients from each band of an image under the IHS color space model. The weights to each gradient are estimated by a systematic method that computes the similarity between the image to compute the gradient and an ”ideal image”, whose histogram has an uniform distribution. Several experiments were done in order to compare the segmentation results provided by the weighted gradient to the results provided by other color space metrics, also according to a subjective criterion, and such comparison is present in this paper.

Object segmentation in image sequences by watershed from markers: a generic approach

We propose a generic method to interactive object segmentation in image sequences. This method consists in the extension of efficient techniques of static image segmentation to image sequences by combining them to fast motion estimation techniques. The proposed method has the following characteristics: interactivity, generality, rapid response and progressive manual edition.