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Small drones are a rising threat due to their possible misuse for illegal activities, in particular smuggling and terrorism. The project SafeShore, funded by the European Commission under the Horizon 2020 program, has launched the “drone-vs-bird detection challenge” to address one of the many technical issues arising in this context. The goal is to detect a drone appearing at some point in a video...
The object detection is a challenging problem in computer vision with various potential real-world applications. The objective of this study is to evaluate the deep learning based object detection techniques for detecting drones. In this paper, we have conducted experiments with different Convolutional Neural Network (CNN) based network architectures namely Zeiler and Fergus (ZF), Visual Geometry...
Video-based human action recognition has become one of the most popular research areas in the field of computer vision and pattern recognition in recent years. It has a wide variety of applications such as surveillance, robotics, health care, video searching and human-computer interaction. There are many challenges involved in human action recognition in videos, such as cluttered backgrounds, occlusions,...
India is a multi-lingual, multi-script country. Considerably less work has been done towards handwritten character recognition of Indian languages than for other languages. In this paper we propose a quadratic classifier based scheme for the recognition of off-line handwritten characters of three popular south Indian scripts: Kannada, Telugu, and Tamil. The features used here are mainly obtained from...
This paper presents the final results of the ICDAR 2015 Competition on Video Script Identification. A description and performance of the participating systems in the competition are reported. The general objective of the competition is to evaluate and benchmark the available methods on word-wise video script identification. It also provides a platform for researchers around the globe to particularly...
Text recognition from video frames is a challenging task due to low resolution, blur, complex and coloured backgrounds, noise, to mention a few. Consequently, the traditional ways of text recognition from scanned documents having simple backgrounds fails when applied to video text. Although there are various techniques available for text recognition from handwritten and printed documents with simple...
Use of multiple scripts for information communication through various media is quite common in a multilingual country. Optical character recognition of such document images or videos assists in indexing them for effective information retrieval. Hence, script identification from multi-lingual documents/images is a necessary step for selecting the appropriate OCR, due the absence of a single OCR system...
The aim of text frame classification technique is to label a video frame as text or non-text before text detection and recognition. It is an essential step prior to text detection because text detection methods assume the input to be a text frame. Consequently, when a non-text frame is subjected to text detection, the precision of the text detection method decreases because of false positives. In...
Script identification at the word level is challenging because of complex backgrounds and low resolution of video. The presence of graphics and scene text in video makes the problem more challenging. In this paper, we employ gradient angle segmentation on words from video text lines. This paper presents new Gradient-Angular-Features (GAF) for video script identification, namely, Arabic, Chinese, English,...
The presence of multiple scripts in multi-lingual document images makes Optical Character Recognition (OCR) of such documents a challenging task. Due to the unavailability of a single OCR system which can handle multiple scripts, script identification becomes an essential step for choosing the appropriate OCR. Although, there are various techniques available for script identification from handwritten...
Script identification is an essential step for the efficient use of the appropriate OCR in multilingual document images. There are various techniques available for script identification from printed and handwritten document images, but script identification from video frames has not been explored much. This paper presents a study of some pre-processing techniques and features for word-wise script...
This paper presents a two-stage method for multi-oriented video character segmentation. Words segmented from video text lines are considered for character segmentation in the present work. Words can contain isolated or non-touching characters, as well as touching characters. Therefore, the character segmentation problem can be viewed as a two stage problem. In the first stage, text cluster is identified...
Word segmentation has become a research topic to improve OCR accuracy for video text recognition, because a video text line suffers from arbitrary orientation, complex background and low resolution. Therefore, for word segmentation from arbitrarily-oriented video text lines, in this paper, we extract four new gradient directional features for each Canny edge pixel of the input text line image to produce...
Text detection in video frames plays a vital role in enhancing the performance of information extraction systems because the text in video frames helps in indexing and retrieving video efficiently and accurately. This paper presents a new method for arbitrarily-oriented text detection in video, based on dominant text pixel selection, text representatives and region growing. The method uses gradient...
Extraction and recognition of text present in video has become a very popular research area in the last decade. Generally, text present in video frames is of different size, orientation, style, etc. with complex backgrounds, noise, low resolution and contrast. These factors make the automatic text extraction and recognition in video frames a challenging task. A large number of techniques have been...
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