An eigen value based approach for text detection in video

Guru, D. S.; Manjunath, S.; Shivakumara, Palaiahnakote; Tan, Chew Lim

doi:10.1145/1815330.1815395

Cited by 12 publications

(7 citation statements)

References 17 publications

(20 reference statements)

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“…The performance evaluation of the proposed approach is done with respect to f-measure(F) which is a combination of two metrics: precision(P) and recall(R) [2]. The truly detected text block (NT DB) is a block with partial or fully detected text.…”

Section: Resultsmentioning

confidence: 99%

Text localization in video/scene images using Kirsch Directional Masks

Shekar

Smitha

2015

2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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Text plays its vital role in visual content analysis and understanding. Videos contain text with diversity in its text patterns and complex backgrounds. In this paper, we propose an approach based on compass operator for detecting the edges. We obtain the edge maps by convolving the Kirsch Directional Masks along eight different directions for the preprocessed video frame. The resultant images are binarized and the edge maps are analyzed and concatenated to obtain a single binarized image. Further, we employ geometrical rules and shape properties to eliminate the false positives. Then, the text regions are identified using connected component analysis and bounding boxes are placed for the detected text regions so that the text gets localized. Experimental results obtained on the standard datasets reveal that the proposed method effectively detect and localize texts of various sizes, fonts and colors in videos and scene images.

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Section: Resultsmentioning

confidence: 99%

Text localization in video/scene images using Kirsch Directional Masks

Shekar

Smitha

2015

2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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“…In this dataset, there are both graphic text and scene text of different languages, e.g. English, Chinese and Korean [20]. We consider 50 video text images to determine the recall, precision and f-measure in this work.…”

Section: Resultsmentioning

confidence: 99%

“…These methods are fast compared to the above two categories. Recently, Eigen based method [20] is proposed to detect text in video where the method explores Eigen value analysis to classify text and non-text pixels for the both low and high resolution images. Since the method involves Eigen value analysis and gradient information, it is said to be expensive and give low precision for complex background images.…”

Section: Introductionmentioning

confidence: 99%

Color and Gradient Features for Text Segmentation from Video Frames

Shivakumara

Guru

Basavaraju

2013

Lecture Notes in Electrical Engineering

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Text segmentation in a video is drawing attention of researchers in the field of image processing, pattern recognition and document image analysis because it helps in annotating and labeling video events accurately. We propose a novel idea of generating an enhanced frame from the R, G, and B channels of an input frame by grouping high and low values using Min-Max clustering criteria. We also perform sliding window on enhanced frame to group high and low values from the neighboring pixel values to further enhance the frame. Subsequently, we use k-means with k=2 clustering algorithm to separate text and non-text regions. The fully connected components will be identified in the skeleton of the frame obtained by k-means clustering. Concept of connected component analysis based on gradient feature has been adapted for the purpose of symmetry verification. The components which satisfy symmetric verification are selected to be the representatives of text regions and they are permitted to grow to cover their respective region fully containing text. The method is tested on variety of video frames to evaluate the performance of the method in terms of recall, precision and f-measure. The results show that method is promising and encouraging

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“…Morphological operations were used to connect the corners. Guru et al [30] proposed an Eigen value based technique, which performs a block wise Eigen analysis on the gradient image of the video frame. Eigen analysis helped in identifying the potential text blocks.…”

Section: Region Based Methodsmentioning

confidence: 99%

Recent Advances in Video Based Document Processing: A Review

Sharma

Pal

Blumenstein

2012

2012 10th IAPR International Workshop on Document Analysis Systems

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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 proposed by various researchers in the recent past to address the problem. This paper presents a review of various state-of-the-art techniques proposed towards different stages (e.g. detection, localization, extraction, etc.) of text information processing in video frames. Looking at the growing popularity and the recent developments in the processing of text in video frames, this review imparts details of current trends and potential directions for further research activities to assist researchers.

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An eigen value based approach for text detection in video

Cited by 12 publications

References 17 publications

Text localization in video/scene images using Kirsch Directional Masks

Text localization in video/scene images using Kirsch Directional Masks

Color and Gradient Features for Text Segmentation from Video Frames

Recent Advances in Video Based Document Processing: A Review

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