• International Journal of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.61-64
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• 2018

In this paper, a pixel value prediction algorithm using edge components in three directions is proposed. There are various directional edges and similarity between adjacent pixels in natural images. After detecting the edge components in the x-axis direction, the y-axis direction, and the diagonal axis direction, the pixel value is predicted by applying the detected edge components and similarity between neighboring pixels. In particular, the predicted pixel value is calculated according to the intensity of the edge component in the diagonal axis direction. Experimental results show that the proposed algorithm can effectively predict pixel values. The proposed algorithm can be used for applications such as reversible data hiding, reversible watermarking to increase the number of embedded data.

• Journal of the Semiconductor & Display Technology
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• v.6 no.2 s.19
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• pp.49-52
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• 2007

Characteristics of an active pixel switch readout circuit were studied by SPICE simulation. A simple readout circuit consists of an operation amplifier, a diode, and a down-counter was suggested, and its successful operation was verified by showing that the differences in the detected signal intensity are accordingly converted to modulation of the voltage pulses generated by the comparator. A scheme to use these pulses to generate the original image was also put forward.

• Proceedings of the KSRS Conference
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• v.2
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• pp.639-642
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• 2006

The intensity-hue-saturation (IHS) technique has become a standard procedure in image analysis. It enhances the colour of highly correlated data. Unfortunately, IHS technique is sensitive to the properties of the analyzed area and usually faces colour distortion problems in the fused process. This paper explores the relationship of colour between before and after the fused process and the change in colour space of images. Subsequently, the fused colours are transformed back into the 'simulative' true colours by the following steps: (1) For each pixel of fused image that match with original pixel (of the coarse spectral resolution image) is transformed back to the true colour of original pixel. (2) The value for interpolating pixels is compensated to preserve the DN ratio between the original pixel and it's vicinity. The 'compensative matrix' is constructed by the DN of fused images and simulation of scaling process. An illustrative example of a Landsat and SPOT fused image also demonstrates the simulative true colour fusion methods.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.312-322
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• 2015

In this paper a new defect detection method for flat panel display that does not require any separately prepared reference images and shows robustness against problems with regard to pixel tolerance and nonuniform illumination condition is proposed. In order to perform defect detection under any magnification value of camera, the proposed method automatically obtains the value of pattern interval through an image analysis. Using the information for pattern interval, an advanced PCSR-G method presented in this paper utilizes neighboring patterns as its reference images instead of utilizing any separately prepared reference images. Also this paper proposes a scheme to improve the performance of the conventional PCSR-G method by extracting and applying additional information for pixel tolerance and intensity distribution considering the value of pattern interval. Simulation results show that the performance of the proposed method utilizing pixel tolerance and intensity distribution is superior to that of the conventional method. Also, it is proved that the proposed method that is implemented using parallel technique based on GPGPU can be applied to real system.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.375-382
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• 2016

In this paper, we presents a signatures verification by using the nonlinear quantization histogram of polar coordinate based on multi-dimensional adjacent pixel intensity difference. The multi-dimensional adjacent pixel intensity difference is calculated from an intensity difference between a pair of pixels in a horizontal, vertical, diagonal, and opposite diagonal directions centering around the reference pixel. The polar coordinate is converted from the rectangular coordinate by making a pair of horizontal and vertical difference, and diagonal and opposite diagonal difference, respectively. The nonlinear quantization histogram is also calculated from nonuniformly quantizing the polar coordinate value by using the Lloyd algorithm, which is the recursive method. The polar coordinate histogram of 4-directional intensity difference is applied not only for more considering the corelation between pixels but also for reducing the calculation load by decreasing the number of histogram. The nonlinear quantization is also applied not only to still more reflect an attribute of intensity variations between pixels but also to obtain the low level histogram. The proposed method has been applied to verified 90(3 persons * 30 signatures/person) images of 256*256 pixels based on a matching measures of city-block, Euclidean, ordinal value, and normalized cross-correlation coefficient. The experimental results show that the proposed method has a superior to the linear quantization histogram, and Euclidean distance is also the optimal matching measure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• Transactions of the Society of Information Storage Systems
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• v.7 no.1
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• pp.42-46
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• 2011

Holographic Data Storage System (HDSS), one of the next generation data storage devices, is a 2-dimensional page oriented memory system using volume hologram. HDSS has many noise sources such as crosstalk, scattering and inter pixel interference, etc. The noise source is changing intensity of the light used for carrying the data signal in HDSS. The inter pixel interference results in decrease of Signal to Noise Ratio and increase of Bit Error Rate. In order to improve these problems, this paper proposes to compensate the inter pixel interference with simple interference mask.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.137-144
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• 2010

Ground digital image data obtained by using DSLR camera can be used to the ground photogrammetry and spatial modeling. Intensity of each pixel in digital video images is the most important parameter to generate digital image. Therefore, it is needed to estimate the parameters and spectral characteristics of digital cameras in order to take more definite intensity data. In this study, using the Sony DSC-F828 DSLR camera, seven digital images are obtained by the continuous shooting. (frame rate, 0.38 seconds). And then extract the value of the intensity from RGB band of each digital color photographs to confirm difference of intensity between frames. The purpose of this study is to confirm spectral characteristics and changes and to estimate correlation through the analysis of statistical in each pixel of R, G, B band.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.331-334
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• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 Pixel. This histogram Is ( x , y ) value of pixel. For example, first line histogram intensity wave from ( 0, 0 ) to ( 0, 197 ) and last wave from ( 280, 0 ) to ( 280, 197 ). So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.

• Journal of Sensor Science and Technology
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• v.18 no.1
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• pp.77-85
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• 2009

We propose a new image pixel architecture which has OFD(Over Flow Device) node by improving conventional 3TR pixel structure. Newly designed pixel consists of photo diode which is verified with HSPICE simulation, PMOS reset transistor, several NMOS and several PMOS transistors. Photodiode signals from each PMOS and NMOS are detected by Reset PMOS. These output signals give enough chances to detect wide operation coverage because OFD node has overflow photocurrent. According to various light intensity, we analyzed characteristic of the output voltage with a SPICE tool. Proposed pixel output has specific value which can detect possible from $0.1{\mu}W/cm^2$ to $10W/cm^2$ light intensity. It has wide-dynamic range of 160 dB.