Rough-fuzzy based scene categorization for text detection and recognition in video

Recognition rate used in this paper to evaluate the performance of the system and the value of recognition rate that achieved of the proposed system is 95.556% of the images are

In recent years, use of multimedia technology has increased tremendously. Among all contents in images, text is found to be one of the most important features

Examples of the text regions and the recognition results from Tesseract OCR using different types of input images, (a) Original color images, (b) MSER images, (c) Color

Shi, et.al [5] proposed a novel approach for scene text detection which used the graph based approach by using Maximally Stable Extremal Regions (MSERs) to

The implemented methodology inn this paper is divided into three main parts: dataset collection that concentrated on fingerprint images, proposed fingerprint recognition

As shown in the last section, the face recognition system proposed in this paper uses the positions of the irises of both eyes to normalize the position, scale and

Combining color and shape information using the methods proposed in this thesis has shown to provide excellent results for object detection and action recognition in still

Unfortunately, one caveat is that these systems have often been too computationally expensive, especially for applica- tion to large images. To apply these algorithms to scene