Fast and robust text detection in images and video frames

Ye, Qixiang; Huang, Qingming; Gao, Wen; Zhao, Debin

doi:10.1016/j.imavis.2005.01.004

Cited by 296 publications

(131 citation statements)

References 26 publications

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“…In all the images recall rate of 99.11, precession rate of 94.67 and overall computed time of 5.28 second can be achieved by the experiment results of the proposed detection method. 88.7 83.9 Liu et al [7] 96.6 91.8 Ye et al [13] 90.8% -Kim et al [14] 82.8 63.7 Li et al [15] 91.1% -Wolf et al [17] 93.5 - Table III shows the performance comparison of our proposed method with other existing text extraction and detection method, where our proposed method has a better performance in precision rate and recall rate. The reason for better recall rate that the proposed method used Gabor filter to change image in to edge based image.…”

Section: Results and Analysismentioning

confidence: 95%

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An Efficient Approach for Text Extraction in Images and Video Frames Using Gabor Filter

Kumar¹

2014

IJCEE

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Abstract-In this paper, an effective methodology for text extraction images and video frames using Gabor filter is proposed. The proposed approach is completed by Gabor Filter, morphological and Heuristic filtering process methods is used to localize the text region better. The proposed technique is completed by text extraction utilizing Gabor filter method which is utilized for text identification within complex images and video frames. Diverse experiments were led to assess the execution of the proposed calculation and algorithm and compare with other methods. Experimental results tested from a large dataset and demonstrated that the proposed method is effective and practical. Various parameters like a precision and recall rates are analyzed for both existing and proposed method to determine the success and limitation of our method. Experiment results show that our method can obtain 99.11 % recall rate and precision rate 94.67 % with average computational time 5.28 second /frames.

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Section: Results and Analysismentioning

confidence: 95%

“…X. Gao et al [12] present algorithms for detection, extraction, binarization and recognition of Chinese video captions. Q. Ye et al [13] proposed a novel coarse-to-fine algorithm that is able to locate text lines even under complex background by using multiscale wavelet features.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Approach for Text Extraction in Images and Video Frames Using Gabor Filter

Kumar¹

2014

IJCEE

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“…Unlike the conventional methods that are based on 2-D DWT, such as Gllavata et al's method [8], the proposed method uses a few lines of 1-D DWT. For low-complexity text line processing, the proposed method examines the high frequency energy over several lines-based on research on the high-frequency energy of text [9,10]. For detecting text lines in the proposed method, the highfrequency signals are selected by an finite impulse response (FIR) high-pass filter of the H1 band of a fourlevel DWT encoder system.…”

Section: Text Line Processingmentioning

confidence: 99%

A Consistent Quality Bit Rate Control for the Line-Based Compression

Ham¹,

Kim²,

Lee³

2016

IEIE Transactions on Smart Processing and Computing

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Abstract:Emerging technologies such as the Internet of Things (IoT) and the Advanced Driver Assistant System (ADAS) often have image transmission functions with tough constraints, like low power and/or low delay, which require that they adopt line-based, low memory compression methods instead of existing frame-based image compression standards. Bit rate control in the conventional frame-based compression systems requires a lot of hardware resources when the scope of handled data falls at the frame level. On the other hand, attempts to reduce the heavy hardware resource requirement by focusing on line-level processing yield uneven image quality through the frame. In this paper, we propose a bit rate control that maintains consistency in image quality through the frame and improves the legibility of text regions. To find the line characteristics, the proposed bit rate control tests each line for ease of compression and the existence of text. Experiments on the proposed bit rate control show peak signal-to-noise ratios (PSNRs) similar to those of conventional bit rate controls, but with the use of significantly fewer hardware resources.

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“…The results prove that it recovers different structural components in the image. The authors in [14] used the texture property to identify the text using SVM. The work in [15] introduces new local thresholding technique "NICK".…”

Section: Related Workmentioning

confidence: 99%

Automatic Detection and Inpainting of Text Images

Bhuvaneswari¹,

Subashini²

2013

IJCA

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The proposed system detects text using connect component labelling and a set of selection/ rejection criteria which helps to retain the text region alone. The detected text region is then inpainted using fast marching algorithm which uses the pixel information that is present in the non-text region of the image for inpainting the detected text region. This work is done in two steps. The first step detects the text region from the image without the user manually marking it and in the second step the text is de-occluded from the image using the existing fast marching inpainting algorithm.

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Fast and robust text detection in images and video frames

Cited by 296 publications

References 26 publications

An Efficient Approach for Text Extraction in Images and Video Frames Using Gabor Filter

An Efficient Approach for Text Extraction in Images and Video Frames Using Gabor Filter

A Consistent Quality Bit Rate Control for the Line-Based Compression

Automatic Detection and Inpainting of Text Images

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