Shanmugalingam Suganthan

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Feature extraction in image data has been investigated for many years, and more recently the problem of processing images containing irregularly distributed data has become prominent. Range data are now commonly used in the areas of image processing and computer vision. However, due to the data irregularity found in range images that occurs with a variety(More)
Real-time extraction of features from range images can play an important role in computer vision tasks such as localisation and navigation. Developing operators that can characterise features in a range image, such as jump, crease, or smooth edges, is challenging, due to both the irregular spatial distribution of range image data and the nature of the(More)
Range images can provide an almost 3-dimensional description of a scene. Feature driven segmentation of range images has been primarily used for 3D object recognition, and hence the accuracy of the detected features is a prominent issue. Feature extraction on range images has proven to be a more complex problem than on intensity images due to both the(More)
The use of range data has become prominent in the field of computer vision. Due to the irregular nature of range data that occurs with a number of sensors, feature extraction is a complex and challenging problem. Feature extraction techniques for range images are often based on scan line data approximations and hence do not employ exact data locations. We(More)
The use of range images has become prominent in the field of computer vision. Due to the irregular nature of range image data that occurs with a number of sensors, edge detection techniques for range images are often based on scan line data approximations and hence do not employ exact data locations. We present a finite element based approach to the(More)