• Journal of Korea Multimedia Society
• /
• v.15 no.9
• /
• pp.1102-1111
• /
• 2012

In this paper, we propose a robust watermarking method against geometric attack even though the watermarked image is partially damaged. This method consists of standard image normalization which transforms any image into a predefined standard image and embedding watermark in DCT domain of standard normalized image using spread spectrum technique. The proposed standard image normalization method has an improvement over existing image normalization method, so it is robust to partial damage and geometric attack. The watermark embedding method using spread spectrum technique also has a robustness to image losses such as blurring, sharpening and compressions. In addition, the proposed watermarking method does not need an original image to detect watermark, so it is useful to public watermarking applications. Several experimental results show that the proposed watermarking method is robust to partial damage and various attacks including geometric deformation.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.3
• /
• pp.27-34
• /
• 2011

In this paper, the novel approach for image contrast enhancement is introduced. The method is based on the unsharp mask and directional information of images. Since the unsharp mask techniques give better visual quality than the conventional sharpening mask, there are much works on image enhancement using unsharp masks. The proposed algorithm decomposes the image to several blocks and extracts directional information using DCT. From the geometric properties of the block, each block is labeled as appropriate type and processed by adaptive unsharp mask. The masking process is skipped at the flat area to reduce the noise artifact, but at the texture and edge area, the adaptive unsharp mask is applied to enhance the image contrast based on the edge direction. Experiments show that the proposed algorithm produces the contrast enhanced images with superior visual quality, suppressing the noise effects and enhancing edge at the same time.

• Journal of IKEEE
• /
• v.25 no.3
• /
• pp.430-436
• /
• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.10
• /
• pp.1234-1239
• /
• 2019

This paper proposes a method for measuring fine dust concentration through digital processing of images captured by only existing CCTVs without additional equipment. This image processing algorithm consists of noise reduction, edge sharpening, ROI setting, edge strength calculation, and correction through HSV conversion. This algorithm is implemented using the C ++ OpenCV library. The algorithm was applied to CCTV images captured over a month. The edge strength values calculated for the ROI region are found to be closely related to the fine dust concentration data. To infer the correlation between the two types fo data, a trend line in the form of a power equation is established using MATLAB. The number of data points deviating from the trend line accounts for around 12.5%. Therefore, the overall accuracy is about 87.5%.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.1 s.307
• /
• pp.9-16
• /
• 2006

This Paper proposes an adaptive error diffusioThis paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, and the MGD values are filled within a local window to merge the potential text segments. Isolated segments are then eliminated in the non-text region filtering process. After the left segmentation, a conventional error diffusion method is applied to the background, while the edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, the gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) prevents the printing of successive dots around the text region boundaries. The error diffusion algorithm with edge enhancement is extended to halftone color images to sharpen the tort regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, the additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. By using the proposed algorithm, the text of a scanned image is sharper than that with a conventional error diffusion without changing background.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.49 no.4
• /
• pp.17-22
• /
• 2012

Convolution filtering methods have been widely applied to various digital signal processing fields for image blurring, sharpening, edge detection, and noise reduction, etc. According to their application purpose, the filter mask size or shape and the mask value are selected in advance, and the designed filter is applied to input image for the convolution processing. In this paper, we proposed an image processing acceleration method for the convolution processing by using two-dimensional Look-up table (LUT) and overlap-region buffering technique. First, based on the fixed convolution mask value, the multiplication operation between 8 or 10 bit pixel values of the input image and the filter mask values is performed a priori, and the results memorized in LUT are referred during the convolution process. Second, based on symmetric structural characteristics of the convolution filters, inherent duplicated operation region is analysed, and the saved operation results in one step before in the predefined memory buffer is recalled and reused in current operation step. Through this buffering, unnecessary repeated filter operation on the same regions is minimized in sequential manner. As the proposed algorithms minimize the computational amount needed for the convolution operation, they work well under the operation environments utilizing embedded systems with limited computational resources or the environments of utilizing general personnel computers. A series of experiments under various situations verifies the effectiveness and usefulness of the proposed methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.6
• /
• pp.463-470
• /
• 2022

Intravenous injection is widely used for patient treatment, including injection drugs, fluids, parenteral nutrition, and blood products, and is the most frequently performed invasive treatment for inpatients, including blood collection, peripheral catheter insertion, and other IV therapy, and more than 1 billion cases per year. Intravenous injection is one of the difficult procedures performed only by experienced nurses who have been trained in intravenous injection, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Nurses who frequently perform intravenous injections may also make mistakes because it is not easy to detect veins due to factors such as obesity, skin color, and age. Accordingly, studies on auxiliary equipment capable of visualizing the venous structure of the back of the hand or arm have been published to reduce mistakes during intravenous injection. This paper is about the development of venous detection equipment that visualizes venous structure during intravenous injection, and the optimal combination was selected by comparing the brightness of acquired images according to the combination of near-infrared (NIR) LED and Filter with different wavelength bands. In addition, an image processing algorithm was derived to threshehold and making blood vessel part to green through grayscale conversion, histogram equilzation, and sharpening filters for clarity of vein images obtained through the implemented venous detection experimental module.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.3
• /
• pp.203-209
• /
• 2021

With the recent development of satellite sensor technology, high-spatial-resolution imagery of various spectral wavelength bands have become possible. Worldview-3 satellite sensor provides panchromatic images with high-spatial-resolution and VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) bands with low-spatial-resolution, so it can be used in various fields such as defense, environment, and surveying. In this study, mineral detection was performed using Worldview-3 satellite imagery. In order to effectively utilize the VNIR and SWIR bands of the Worldview-3 satellite image, the sharpening technique was applied to the spatial resolution of the panchromatic image. To confirm the utility of SWIR bands for mineral detection, mineral detection using only VNIR bands was performed and comparatively evaluated. As the mineral detection technique, SAM (Spectral Angle Mapper), a representative similarity technique, was applied, and the pixels detected as minerals were selected by applying an empirical threshold to the analysis result. Quantitative evaluation was performed using reference data on the results of similarity analysis to evaluate the accuracy of mineral detection. As a result of the accuracy evaluation, the detection rate and false detection rate of mineral detecting using SWIR bands were calculated to be 0.882 and 0.011, respectively, and the results using only VNIR bands were 0.891 and 0.037, respectively. It was found that the detection rate when the SWIR bands were additionally used was lower than that when only the VNIR bands were used. However, it was found that the false detection rate was significantly reduced, and through this, it was possible to confirm the applicability of SWIR bands in mineral detection.