• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1852-1859
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• 2016

The effectiveness of a binarization algorithm in image processing depends on how to eliminate the uncertainty of determining threshold in a reasonable way and on minimizing information loss due to the binarization effect. Fuzzy binarization technique was proposed to handle that uncertainty with fuzzy logic. However, that method is known to be inefficient when the given image has low intensity contrast. In this paper, we propose an improved fuzzy binarization method to overcome such known drawbacks. Our method proposes a trapezoid type fuzzy membership function instead of most-frequently used triangle type one. We also propose an adaptive ${\alpha}$_cut determination policy. Our proposed method has less information loss than other algorithms since we do not use any stretching based preprocessing for enhancing the intensity contrast. In experiment, our proposed method is verified to be more effective in binarization with less information loss for many different types of images with low intensity contrast such as night scenery, lumber scoliosis, and lipoma images.

• Journal of IKEEE
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• v.18 no.3
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• pp.356-361
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• 2014

This paper proposes hardware architecture of HEVC (high efficiency video coding) CABAC (context-based adaptive binary arithmetic coding) binarizer. The proposed binarizer was designed and implemented as an independent module that can be integrated into HEVC CABAC encoder. It generates each bin string of each syntax element in a single cycle. It consists of controller module, TU (truncated unary binarization) module, TR (truncated Rice binarization) module, FL (fixed length binarization) module, EGK (k-th order exp-Golomb coding) module, CALR (coeff_abs_level_remaining) module, QP Delta (cu_qp_delta_abs) module, Intra Pred (intra_chroma_pred_mode) module, Inter Pred (inter_pred_idc) module, and Part Mode (part_mode) module. The proposed binarizer was designed in Verilog HDL, and it was implemented in 45 nm technology. Its operating speed, gate count, and power consumption are 200 MHz, 1,678 gates, and 50 uW, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.108-114
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• 2003

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method (called adaptive logical thresholding method) for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.18-26
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• 2015

Geometric distortion and shadow effect due to capturing angle could be included in document copy images that are captured by a camera in stead of a scanner. In this paper, a clean black and white document image generation algorithm by distortion correction and shadow elimination based on a camera, is proposed. In order to correct geometric distortion such as straightening un-straight boundary lines occurred by camera lens radial distortion and eliminating outlying area included by camera direction, second derivative filter based document boundary detection method is developed. Black and white images have been generated by adaptive binarization method by eliminating shadow effect. Experimental results of the black and white document image generation algorithm by recovering geometrical distortion and eliminating shadow effect for the document images captured by smart phone camera, shows very good processing results.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.49-54
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• 2014

This paper proposes a new color segmentation method of vehicle license plates in the RGB color space. Firstly, the proposed method shifts the histogram of an input image rightwards and then stretches the image of the histogram slide. Secondly, the method separates each of the three RGB color components and performs the adaptive threshold processing with the three components, respectively. Finally, it combines the three components under the condition of making up a segment color and removes noises with the morphological processing. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real vehicle images. The results show that the proposed algorithm is successful for most vehicle images. However, the method fails in some vehicles when the body and the license plate have the same color.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.608-618
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• 2007

Image binarization is an important preprocessing to identify the object of interest by dividing pixels into the background and object. We proposes efficient binarization method and a stroke reconstruction method of the low quality character image for an effective character recognition. First, the character image is binarized by using the both advantages of local and global thresholding method and then the noise elimination around the character stroke and the hole filling on the stoke by the analysis of the binarized stroke image are performed to enhance the quality of the character stroke. Proposed binarization algorithm for character image achieved an efficiency of both processing speed and performance by the adaptive threshold selection. Moreover, We could get a high qualify binary image by a stroke reconstruction of the step-by-step denoising process.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.143-147
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• 1998

카메라 영상에 의한 자동차 번호판 인식시스템은 영상 획득, 번호판 추출, 전처리, 문자 분리, 문자 인식 등 크게 5자기의 핵심 부분으로 구성된다. 따라서 자동차 번호판 인식시스템의 성능을 향상시키기 위해서는 이들 부분들 각각의 성능의 최적화가 필요하다. 본 연구는 자동차 번호판 인식시스템의 여러 단계 중 전처리에 해당하는 번호판 영역의 이진화에 관한 연구로서, 기존의 단일 임계치 방법과 다중 임계치 방법이 해결하지 못했던 부분을 보완하는 새로운 다중 임계치 방법을 제안한다. 본 논문에서 제안하는 다중 임계치 알고리즘(Adaptive Multi-threshold Algorithm)을 사용함으로써 gray-level 번호판 영상에 대해서 보다 깨끗한 이진 영상을 얻을 수 있었으며, 또한 이 알고리즘은 번호판 영역의 밝기값이 고르지 않은 영상에 대해서도 효율적인 알고리즘 임을 알 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.65-68
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• 2006

카메라로 촬영한 문서 영상의 분석 및 인식을 위한 적응적 이진화 방법을 제안한다. 먼저 카메라 영상의 화질을 분석하여 정량화하는 방법을 제안한다. 그 후 다양한 화질의 카메라 영상에 대하여 제안한 방법으로 측정한 화질과 그 화질에 적합한 이진화 파라미터간의 상관 관계를 통계적으로 분석한다. 그 후 그들간의 상관 관계를 이용하여 입력 영상의 화질에 적합한 이진화 파라미터를 자동으로 추정하도록 함으로써 화질 변화에 대한 적응력을 강화하였다. 실험을 통해 초점 및 잡영의 상태에 따라 적절한 파라미터를 추정함으로써 화질 변화에 적응하는 결과를 확인하였다.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.368-375
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• 2010

Unlike document images, license plate images are mostly captured under uneven lighting conditions. In particular, a shadowed region has sharp intensity variation and sometimes that region has very high intensity by reflected light. This paper presents a new technique for thresholding license plate images. This approach consists of three parts. In the first part, it performs a rough thresholding and classifies the type of license plate to adjust some parameters optimally. Next, it identifies a shadow type and binarizes license plate images by adjusting the window size and location according to the shadow type. And finally, post-processing based on the cluster analysis is performed. Experimental results show that the proposed method outperformed five well-known methods.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.737-744
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• 2005

In this paper, we propose a three-level color clustering algerian for the binarization of text regions extracted from natural scene images. The proposed algorithm consists of three phases of color segmentation. First, the ordinary images in which the texts are well separated from the background, are binarized. Then, in the second phase, the input image is passed through a high pass filter to deal with those affected by natural or artificial light. Finally, the image Is passed through a low pass filter to deal with the texture in texts and/or background. We have shown that the proposed algorithm is more effective used gray-information binarization algorithm. To evaluate the effectiveness of the proposed algorithm we use a commercial OCR software ARMI 6.0 to observe the recognition accuracies on the binarized images. The experimental results on word and character recognition show that the proposed approach is more accurate than conventional methods by over $35\%$.