Vgnezdene izbočene lupine kot značilnice za zaznavo dvojnikov digitalnih slik in video posnetkov : doktorska disertacija

slovenian

doktorska dela

2011

Univerza v Mariboru, Fakulteta za elektrotehniko računalništvo in informatiko

Doctoral dissertation deals with the searching of near-duplicate images and video clips. From the picture, we form a geometric feature; convex layers, which are later converted into a feature vector. The thesis derives two algorithms for extraction the feature vector from images. In the first algorithm, convex layers are extracted from a binary image, while in the second one the feature is extracted from a sequence of binary images. In this case, the convex layers are constructed for all images in the sequence. Pixels of images are considered located on the raster. For raster points we developed an algorithm to construct convex layers in the linear time, thus itstime complexity depends only on the resolution of images. For feature vectors, we developed new measure of similarity. It measures the distance called neighbourhood relations distance. From the feature vector, four coefficients are calculated. The coefficients describe the monotony of the vector function. The local area neighbourhood distance is a function of differences and sums of four coefficients. The thesis also describes the extension of serial binary images features algorithm and local area neighbourhood distance into the area of near-duplicate video clip detection. The effectiveness test of the developed algorithms was performed. The image duplicate detection efficiency is highest in serial binary images features algorithm in combination with the correlation coefficient. Lowest computational complexity was obtained by the algorithm based on binary image feature, but the algorithm of serial binary features does not lag much. Also, performance and time efficiency are also very good for the developed algorithm when detecting duplicated videos.

07.08.2023