Koen Douterloigne

Fully automatic and robust UAV camera calibration using chessboard patterns

Due to weight constraints, UAVs often carry cameras with lenses that create distortions in the image. For practical applications this distortion should be removed with a proper calibration procedure, without spending too much extra time. Existing methods require costly manual interaction when the grid is not fully visible, or when not all points can be extracted. In this paper we present an algorithm to perform the calibration without any user interaction whatsoever, which works under almost all possible conditions. The only inputs are a number of pictures of a checkerboard, taken with the camera. We extract the corners from the chessboard pictures, and set up a world coordinate grid that is robust to missing corner points, occlusion and deformations. We automatically omit the pictures that are too close to another picture, to avoid giving too much weight to often viewed areas. Finally we optimize the result by iteratively removing outlier pictures from the set.

On the accuracy of 3D landscapes from UAV image data

Our surroundings change all the time. Applications that require 3D models of a changing terrain, such as urban planning, are becoming ever more demanding with respect to the cost to create them and the accuracy of the result. A novel, cheap and fast solution for this problem is given by a UAV to take aerial images of the terrain in question, in combination with structure from motion algorithms to create a 3D model from those aerial images. However the question remains whether these on-the-fly 3D maps can match the accuracy of classical surveyor based models, which require more time to create. In this paper we investigate this question, and find that under certain conditions the accuracy of the UAV based model matches the accuracy of surveyor generated measurements.

A novel dictionary based computer vision method for the detection of cell nuclei.

Cell nuclei detection in fluorescent microscopic images is an important and time consuming task in a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make individual nuclei detection a challenging task for automated image analysis. This paper proposes a novel and robust detection method based on the active contour framework. Improvement over conventional approaches is achieved by exploiting prior knowledge of the nucleus shape in order to better detect individual nuclei. This prior knowledge is defined using a dictionary based approach which can be formulated as the optimization of a convex energy function. The proposed method shows accurate detection results for dense clusters of nuclei, for example, an F-measure (a measure for detection accuracy) of 0.96 for the detection of cell nuclei in peripheral blood mononuclear cells, compared to an F-measure of 0.90 achieved by state-of-the-art nuclei detection methods.

A non-rigid registration method for multispectral imaging of plants

Registration of multispectral images remains a challenging task due to the lack of stable feature points. Methods based on intensities are generally more robust for multi-modal image registration, but are computationally demanding or are restrictive to the transformation model allowed in the registration. This paper proposes a new registration framework which overcomes these drawbacks. The proposed method optimizes the location of a set of virtual landmarks in order to get robust and accurate registration.

Correction, stitching and blur estimation of micro-graphs obtained at high speed

Micro-structures of surface are considered to be effective in identifying the damage mechanisms. The industry uses computer vision to auto detect misalignment of the components as it is a contactless tool. However, in scientific investigations micro structures obtained online at high-speed has to be analyzed. In this work the change detection of a specimen rotating at a high speed studied online using image processing techniques in micro graphs which provides a clear insight about the dimensional changes. The specimen under study is made from polymer composite which has contact with a steel wheel and rotates at a high speed. The blur as a measure of dimensional change of the polymer composite can be identified due to the change in focus. The micro-structure images were dark and span a very small region of the surface due to high speed image acquisition, short shutter time and magnification of the microscope. Thus, pre-processing procedures like image enhancement, stitching and registration are performed. Then 15 blur estimation methods are applied to the stitched images. The results of three methods present a good correlation with dimensional change provided by a stylus instrument.

Automatic and robust extrinsic camera calibration for high-accuracy mobile mapping

A mobile mapping system (MMS) is the answer of the geoinformation community to the exponentially growing demand for various geospatial data with increasingly higher accuracies and captured by multiple sensors. As the mobile mapping technology is pushed to explore its use for various applications on water, rail, or road, the need emerges to have an external sensor calibration procedure which is portable, fast and easy to perform. This way, sensors can be mounted and demounted depending on the application requirements without the need for time consuming calibration procedures. A new methodology is presented to provide a high quality external calibration of cameras which is automatic, robust and fool proof.The MMS uses an Applanix POSLV420, which is a tightly coupled GPS/INS positioning system. The cameras used are Point Grey color video cameras synchronized with the GPS/INS system. The method uses a portable, standard ranging pole which needs to be positioned on a known ground control point. For calibration a well studied absolute orientation problem needs to be solved. Here, a mutual information based image registration technique is studied for automatic alignment of the ranging pole. Finally, a few benchmarking tests are done under various lighting conditions which proves the methodology’s robustness, by showing high absolute stereo measurement accuracies of a few centimeters.

2D mapping of strongly deformed cell nuclei based on contour warping

The dynamics of genome regions are associated to the functional or dysfunctional behaviour of the human cell. In order to study these dynamics it is necessary to remove perturbations coming from movement and deformation of the nucleus, i.e. the container holding the genome. In literature models have been proposed to cope with the transformations corresponding to nuclear dynamics of healthy cells. However for pathological cells, the nucleus deforms in an apparently random way, making the use of such models a non trivial task. In this paper we propose a mapping of the cell nucleus which is based on the matching of the nuclear contours. The proposed method does not put constraints on the possible shapes nor on the possible deformations, making this method suited for the analysis of pathological nuclei.

Per Pixel Contextual Information for Classification of VHR Images of Urban Areas

Very high spatial resolution satellite images allow to identify individual man-made objects. However, automatic extraction of these objects is still very difficult, especially in urban areas. Spectral information is insufficient to separate the different man-made object classes. Therefore, there is an increased interest in incorporating shape and contextual information in the classification process. Object-based approaches provide a straightforward method to incorporate both shape and contextual information. However, these approaches require a segmentation of the image, which is a very difficult and sensitive task, especially in urban areas. Recently some attempts have been made to incorporate shape information on a pixel basis. In this paper we further develop this approach and propose a method to also derive contextual information on a pixel basis. The per-pixel features developed in this paper contain information about the distance from the object the pixel belongs to to the nearest shadow object. Clearly, this information can be helpful to identify buildings, which are generally accompanied by shadow. However, the proposed method can also be used to describe other contextual information.

Registration of vector data and aerial thermal images using modified mutual information

The topic of registering multi- and hyperspectral imagery is well studied in literature. However when the registration must be done between multispectral images and vector data, the literature is more limited. In this paper we focus on registering aerial images in the thermal (IR) band, and vector data delineating houses and other man-made structures in the same region. This differs from classical registration because first of all, the vector data is not in the same format as the thermal image (i.e. vectors versus pixels), although it can be rasterized initially. Secondly, feature points fail to match between the two representations while intensity based methods also have problems due to the large changes between the rasterized vector and thermal images. We present a method based on a modified version of mutual information that outperforms existing methods for these specific inputs.

A comparative study on the optimization of global optimum active contours

The active contour framework is widely used for segmentation of images. Specially active contours with a convex energy gained a lot of interest, since they are independent of initialization. Several methods have been proposed to minimise the active contour energy, all claiming to be fast and efficient. In this paper we study and compare the convergence and constraints of these methods. We also propose a new optimization method specially designed for the optimization of convex energy active contours. The proposed method is a combination of a line search method with a Newton-Raphson optimization technique. The proposed method shows good convergence results, while maintaining a low computation cost.