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In recent years, the use of imaging based, non-invasive, and non-destructive plant phenotyping platforms have become popular. The analysis of the imaging data acquired from these platforms is still challenging. Current, 2D methods are limited in the information available, while 3D methods are more challenging to analyze. Plants like wheat are particularly challenging due to their thin leaves which...
Monitoring of rock fragmentation is a commercially important problem for the mining industry. Existing analysis methods either resort to physically sieving rock samples, or using image analysis software. The currently available software systems for this problem typically work with 2D images and often require a significant amount of time by skilled human operators, particularly to accurately delineate...
Image segmentation seeks to partition the pixels in images into distinct regions to assist other image processing functions such as object recognition. Over the last few years dictionary learning methods have become very popular for image processing tasks such as denoising, and recently structured low rank dictionary learning has been shown to be capable of promising results for recognition tasks...
Image matting is the process of extracting the foreground component from an image. Since matting is an under constrained problem most techniques address the case where users supply some dense labelling to indicate known foreground and background regions. In contrast to other techniques our proposed technique is unique in that focuses on achieving satisfactory results with extremely sparse input, e...
This paper proposes a method for supervised classification using Low-Rank Representation of transposed data. Recent papers have suggested that low rank representation of transposed data may be useful for feature extraction. We develop an algorithm called TLRRC for supervised classification using transposed data and demonstrate that its performance is competitive with state-of-the-art classification...
The chordiogram has recently been proposed for detection and segmentation of shapes in images. This paper evaluates the effectiveness of using chordiograms for recognizing hand written characters using the MNIST dataset. The method calculates a feature for each digit based on the geometric relationships of boundary pixels. The resultant features are used to train a support vector machine which is...
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