2 resultados para Techniques: Image Processing

em Helda - Digital Repository of University of Helsinki


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The aim of the thesis was to compare the correspondence of the outcome a computer assisted program appearance compared to the original image. The aspect of the study was directed to embroidery with household machines. The study was made from the usability point of view with Brother's PE-design 6.0 embroidery design programs two automatic techniques; multicoloured fragment design and multicoloured stitch surface design. The study's subject is very current because of the fast development of machine embroidery. The theory is based on history of household sewing machines, embroidery sewing machines, stitch types in household sewing machines, embroidery design programs as well as PE-design 6.0 embroidery design program's six automatic techniques. Additionally designing of embroidery designs were included: original image, digitizing, punching, applicable sewing threads as well as the connection between embroidery designs and materials used on embroidery. Correspondences of sewn appearances were examined with sewing experimental methods. 18 research samples of five original image were sewn with both techniques. Experiments were divided into four testing stages in design program. Every testing stage was followed by experimental sewing with Brother Super Galaxie 3100D embroidery machine. Experiments were reported into process files and forms made for the techniques. Research samples were analysed on images syntactic bases with sensory perception assessment. Original images and correspondence of the embroidery appearances were analysed with a form made of it. The form was divided into colour and shape assessment in five stage-similarity-scale. Based on this correspondence analysis it can be said that with both automatic techniques the best correspondence of colour and shape was achieved by changing the standard settings and using the makers own thread chart and edited original image. According to the testing made it is impossible to inform where the image editing possibilities of the images are sufficient or does the optimum correspondence need a separate program. When aiming at correspondence between appearances of two images the computer is unable to trace by itself the appearance of the original image. Processing a computer program assisted embroidery image human perception and personal decision making are unavoidable.

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The usual task in music information retrieval (MIR) is to find occurrences of a monophonic query pattern within a music database, which can contain both monophonic and polyphonic content. The so-called query-by-humming systems are a famous instance of content-based MIR. In such a system, the user's hummed query is converted into symbolic form to perform search operations in a similarly encoded database. The symbolic representation (e.g., textual, MIDI or vector data) is typically a quantized and simplified version of the sampled audio data, yielding to faster search algorithms and space requirements that can be met in real-life situations. In this thesis, we investigate geometric approaches to MIR. We first study some musicological properties often needed in MIR algorithms, and then give a literature review on traditional (e.g., string-matching-based) MIR algorithms and novel techniques based on geometry. We also introduce some concepts from digital image processing, namely the mathematical morphology, which we will use to develop and implement four algorithms for geometric music retrieval. The symbolic representation in the case of our algorithms is a binary 2-D image. We use various morphological pre- and post-processing operations on the query and the database images to perform template matching / pattern recognition for the images. The algorithms are basically extensions to classic image correlation and hit-or-miss transformation techniques used widely in template matching applications. They aim to be a future extension to the retrieval engine of C-BRAHMS, which is a research project of the Department of Computer Science at University of Helsinki.