Trademark recognition using the PDH shape descriptor

The paper presents the results of experiments, where trademark shapes were described using the PDH algorithm and recognized using the template matching approach. Those experiments were performed to verify some properties of the PDH shape descriptor in the presence of real contour object deformations

Polar contour shape descriptors in the template matching approach to object recognition

The paper provides a review of contour polar shape descriptors used in recognition of objects based on their silhouettes. The process of recognition in the template matching approach has to be based on so called descriptors, assigned to object features, e.g. shape, texture, color, luminance, context of the information and movement. Amongst them very special attention is paid to the shape, because in many applications it is the most relevant and the less changeable feature that can be used.The shape in the digital image processing has usually a form of binary object. One of the representations uses the boundary, contour of a silhouette. The most important advantage of such approach is a small number of pixels to consider.Amongst several dozen shape descriptors special properties can be found in the polar ones, which use the transformation from the Cartesian to the polar coordinates. The most important is invariance to translation of the object points. The rotation becomes a circular shift what can be easily solved in further processing. Owing to the normalization the descriptors can be also invariant to scaling. Some of the methods are also robust to some level of noise and occlusion

Trademark recognition using the PDH shape descriptor

The paper presents the results of experiments, where trademark shapes were described using the PDH algorithm and recognized using the template matching approach. Those experiments were performed to verify some properties of the PDH shape descriptor in the presence of real contour object deformations

Current challenges in content based image retrieval by means of low-level feature combining

The aim of this paper is to discuss a fusion of the two most popular low-level image features - colour and shape - in the aspect of content-based image retrieval. By combining them we can achieve much higher accuracy in various areas, e.g. pattern recognition, object representation, image retrieval. To achieve such a goal two general strategies (sequential and parallel) for joining elementary queries were proposed. Usually they are employed to construct a processing structure, where each image is being decomposed into regions, based on shapes with some characteristic properties - colour and its distribution. In the paper we provide an analysis of this proposition as well as the exemplary results of application in the Content Based Image Retrieval problem. The original contribution of the presented work is related to different fusions of several shape and colour descriptors (standard and non-standard ones) and joining them into parallel or sequential structures giving considerable improvements in content-based image retrieval. The novelty is based on the fact that many existing methods (even complex ones) work in single domain (shape or colour), while the proposed approach joins features from different areas

Wybrane problemy bezstratnej kompresji obrazów binarnych

In the paper some basic notions and algorithms devoted to the problem of lossless digital binary images compressionwere provided. A brief survey on existing lossless algorithms was performed, concentrated on the ones that are or can be applied tobinary images, e.g. Huffman, Golomb, Rice, JBIG, RLE, arithmetic coding, as well as the selected predicting approaches.W artykule przedstawiono podstawowe pojęcia i algorytmy związane z bezstratną kompresją obrazów binarnych. Dokonano przeglądu istniejących algorytmów bezstratnej kompresji, które są lub mogą być stosowane do obrazów binarnych, takich jak: kodowanie Huffmana, Golomba, Rice’a, kompresja JBIG, kodowanie długości sekwencji, kodowanie arytmetyczne oraz wybrane algorytmy predykcyjn

A discussion on selected problems of lossless binary digital images compression

In the paper some basic notions and algorithms devoted to the problem of lossless digital binary images compression were provided. A brief survey on existing lossless algorithms was performed, concentrated on the ones that are or can be applied to binary images, e.g. Huffman, Golomb, Rice, JBIG, RLE, arithmetic coding, as well as the selected predicting approaches.W artykule przedstawiono podstawowe pojęcia i algorytmy związane z bezstratną kompresją obrazów binarnych. Dokonano przeglądu istniejących algorytmów bezstratnej kompresji, które są lub mogą być stosowane do obrazów binarnych, takich jak: kodowanie Huffmana, Golomba, Rice’a, kompresja JBIG, kodowanie długości sekwencji, kodowanie arytmetyczne oraz wybrane algorytmy predykcyjne

Przegląd podstawowych metod reprezentacji kształtów 3D

In the paper a brief survey on existing approaches to the representation of three-dimensional shapes was presented. It is a new way of describing objects in image processing, recognition and indexing. The 3D shape descriptors become more and more useful and widely used. Rapid development of computer hardware and the possibilities of fast processing of three-dimensional scenes cause it. Many new applications of 3D shape description can be easily found, e.g. in biometrics, CAD systems and image retrieval.W artykule przedstawiono przegląd istniejących rozwiązań w dziedzinie reprezentowania kształtów trójwymiarowych, stosunkowo nowym podejściu do opisywania obiektów w przetwarzaniu, rozpoznawaniu i indeksowaniu obrazów.Deskryptory kształtu 3D stają się coraz potrzebniejsze i coraz powszechniej stosowane. Wynika to z rozwoju sprzętu komputerowego, a co za tym idzie możliwości szybkiego przetwarzania skomplikowanych scen trójwymiarowych. Znajduje się przy tym kolejne obszary zastosowań trójwymiarowego opisu obiektów, m.in. w biometrii, systemach CAD i indeksowaniu

A discussion on selected problems of lossless binary digital images compression

In the paper a brief survey on existing approaches to the representation of three-dimensional shapes was presented. It is a new way of describing objects in image processing, recognition and indexing. The 3D shape descriptors become more and more useful and widely used. Rapid development of computer hardware and the possibilities of fast processing of three-dimensional scenes cause it. Many new applications of 3D shape description can be easily found, e.g. in biometrics, CAD systems and image retrieval.W artykule przedstawiono przegląd istniejących rozwiązań w dziedzinie reprezentowania kształtów trójwymiarowych, stosunkowo nowym podejściu do opisywania obiektów w przetwarzaniu, rozpoznawaniu i indeksowaniu obrazów. Deskryptory kształtu 3D stają się coraz potrzebniejsze i coraz powszechniej stosowane. Wynika to z rozwoju sprzętu komputerowego, a co za tym idzie możliwości szybkiego przetwarzania skomplikowanych scen trójwymiarowych. Znajduje się przy tym kolejne obszary zastosowań trójwymiarowego opisu obiektów, m.in. w biometrii, systemach CAD i indeksowaniu