Обнаружение текстовых областей в видеопоследовательностях

В статье рассматривается задача обнаружения текстовых областей на неоднородном фоне в видео-последовательностях. Предлагается двухэтапная схема, алгоритм и методика обнаружения текстовых областей с использованием непрерывного вейвлет-преобразования с автоматическим выбором масштаба или итерационной обработкой с разными масштабами.У статті розглядається задача виявлення текстових областей на неоднорідному фоні в відеопослідовності. Пропонується двоетапна схема, алгоритм і методика виявлення текстових областей з використанням безперервного вейвлет-перетворення з автоматичним вибором масштабу або ітераційною обробкою з різними масштабами.In the article, the problem of text region detection on the non-uniform background in video frames is considered. The two-stage scheme, the algorithm and the technique of detection of text regions using a continuous wavelet transform with automatic scale selection or iteration processing at different scales are poposed

Information retrieval in multimedia databases using relevance feedback algorithms. Applying logistic regression to relevance feedback in image retrieval systems

This master tesis deals with the problem of image retrieval from large image databases. A particularly interesting problem is the retrieval of all images which are similar to one in the user's mind, taking into account his/her feedback which is expressed as positive or negative preferences for the images that the system progressively shows during the search. Here, a novel algorithm is presented for the incorporation of user preferences in an image retrieval system based exclusively on the visual content of the image, which is stored as a vector of low-level features. The algorithm considers the probability of an image belonging to the set of those sought by the user, and models the logit of this probability as the output of a linear model whose inputs are the low level image features. The image database is ranked by the output of the model and shown to the user, who selects a few positive and negative samples, repeating the process in an iterative way until he/she is satisfied. The problem of the small sample size with respect to the number of features is solved by adjusting several partial linear models and combining their relevance probabilities by means of an ordered weighted averaged (OWA) operator. Experiments were made with 40 users and they exhibited good performance in finding a target image (4 iterations on average) in a database of about 4700 imagesZuccarello, PD. (2007). Information retrieval in multimedia databases using relevance feedback algorithms. Applying logistic regression to relevance feedback in image retrieval systems. http://hdl.handle.net/10251/12196Archivo delegad

MULTIRESOLUTION TEXT DETECTION IN VIDEO FRAMES

Abstract: This paper proposes an algorithm for detecting artificial text in video frames using edge information. First, an edge map is created using the Canny edge detector. Then, morphological dilation and opening are used in order to connect the vertical edges and eliminate false alarms. Bounding boxes are determined for every non-zero valued connected component, consisting the initial candidate text areas. Finally, an edge projection analysis is applied, refining the result and splitting text areas in text lines. The whole algorithm is applied in different resolutions to ensure text detection with size variability. Experimental results prove that the method is highly effective and efficient for artificial text detection.