• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.332-335
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• 2013

In this paper, we propose an image retrieval method using an EHD (Edge Histogram Descriptor) of MPEG-7 and the color histogram. The EHD algorithm can be used to collect the gradient of edge distribution and to find a similar image. However, if you only search the edge gradient without considering the image color, the color shows a weakness. In order to overcome this problem, we use the color histogram and extract the feature to determine whether a similar image. The proposed method shows that the weakness of existing EHD can be overcome by using the color histogram.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2007.02a
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• pp.127-133
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• 2007

We propose new reversible watermarking method for images. Being reversibility, original image and watermarked message should be recovered exactly. We propose different technique for hiding data to pairs. We use new type of histogram (pair histogram), which shows frequencies of each pair in image. We use histogram shift method for data embedding to pairs. We also propose improved version of method which allow hiding data with good performance for high capacities. This algorithm has better result compare to Tian's difference expansion method based on the Haar wavelet decomposition. For proposed algorithm capacity is higher under same PSNR.

• ETRI Journal
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• v.28 no.4
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• pp.502-505
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• 2006

A new class-based histogram equalization method is proposed for robust speech recognition. The proposed method aims at not only compensating the acoustic mismatch between training and test environments, but also at reducing the discrepancy between the phonetic distributions of training and test speech data. The algorithm utilizes multiple class-specific reference and test cumulative distribution functions, classifies the noisy test features into their corresponding classes, and equalizes the features by using their corresponding class-specific reference and test distributions. Experiments on the Aurora 2 database proved the effectiveness of the proposed method by reducing relative errors by 18.74%, 17.52%, and 23.45% over the conventional histogram equalization method and by 59.43%, 66.00%, and 50.50% over mel-cepstral-based features for test sets A, B, and C, respectively.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.358-365
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• 2014

This paper proposes a method that reduces the flickering effect caused by A-GLG (Adaptive Gray-Level Grouping) during video contrast enhancement. Of the GLG series, A-GLG shows the best contrast enhancement performance. The GLG series is based on histogram grouping. Histogram grouping is calculated differently between the continuous frames with a similar histogram and causes a subtle change in the transformation function. This is the reason for flickering effect when the video contrast is enhanced by A-GLG. To reduce the flickering effect caused by A-GLG, the proposed method calculates a modified transformation function. The modified transformation function is calculated using a previous and current transformation function applied with a weight separately. The proposed method was compared with A-GLG for flickering effect reduction and video contrast enhancement. Through the experimental results, the proposed method showed not only a reduced flickering effect, but also video contrast enhancement.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.453-467
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• 2014

A typical histogram equalization contrast enhancement effect for improving the image quality is excellent. However, because it appears that excessive changes of the brightness values, The average brightness of the image is changing in units of frames of applications such as a TV video is unsuitable. In order to solve these drawbacks, a modified method of histogram equalization on various studies have been made. But the result images of existing methods sometimes shown visual degradations such as over-enhancement and false contouring. In this paper, we propose improved contrast enhancement method through bi-histogram equalization using target mean brightness based on differential compression method. The proposed method is based on the average brightness value by dividing the histogram, the histogram for each zone, according to the frequency differential of compression. And equalize the modified histogram based on target mean brightness. This allows to suppress deterioration of picture quality, and changes in the average brightness of each frame of video, while maintaining and improving the contrast. Experimental results show that the proposed method compared to the conventional method, the average brightness of each frame from a movie well maintained, and no degradation of the image quality showed a good effect to improve the contrast.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.645-655
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• 2013

As one of segmentation techniques for Synthetic Aperture Radar (SAR) image with oil spill, we applied a bimodal histogram method to discriminate oil pixels from non-oil pixels. The threshold of each moving window was objectively determined using the two peaks in the histogram distribution of backscattering coefficients from ENVISAT ASAR image. To reduce the effect of wind speed on oil spill detection, we selected ASAR image which satisfied a limit of wind speeds for successful detection. Overall, a commonly used adaptive threshold method has been applied with a subjectively-determined single threshold. In contrast, the bimodal histogram method utilized herein produces a variety of thresholds objectively for each moving window by considering the characteristics of statistical distribution of backscattering coefficients. Comparison between the two methods revealed that the bimodal histogram method exhibited no significant difference in terms of performance when compared to the adaptive threshold method, except for around the edges of dark oil spots. Thus, we anticipate that the objective method based on the bimodality of oil slicks may also be applicable to the detection of oil spills from other SAR imagery.

• Journal of Veterinary Clinics
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• v.16 no.1
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• pp.118-127
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• 1999

The aim of this study was to establish the method of differential diagnosis between developing and regressing corpus luteum in cows. Plasma progesterone (P$_4$) concentrations were determined by radioimmunoassay in slaughtered, cycling and pregnant cows. Ultrasonography was used to measure the corpus luteum size and histogram values for determining the correlationships between corpus luteum area or histogram values and plasma P$_4$ concentrations. The corpora lutea were monitored in vitro (water-bath scanning) by using ultrasonography with 7.5 MHz linear-array transducer in 196 slaughtered cows. The correlation coefficient between corpus luteum area and plasma P$_4$ concentrations was 0.46 (p<0.01), and between histogram values and plasma P$_4$ concentrations was -0.44 (p<0.01), respectively. The corpora lutea were monitored by ultrasonography with 5.0 MHz linear-array transrectal transducer in 188 cycling and 30 pregnant cows. The corpus luteum areas and plasma P4 concentrations were significantly different between regressing and other corpora lutea (p<0.01), and also histogram values were significantly different between regressing and developing corpola lutea (p＜0.01). The correlation coefficients between corpus luteum areas and plasma P$_4$ concentrations were 0.76 (p<0.01), 0.71 (p<0.01), 0.65 (p＜0.05) and 0.68 (p<0.05), and between histogram values and plasma P$_4$ concentrations were 0.74 (p<0.05), 0.71 (p＜0.01), -0.52 (p<0.05) and 0.65 (p＜0.05) in developing, functional, regressing and pregnant corpora lutea, respectively. These results indicate that corpus luteum areas and plasma P$_4$ concentrations were highly correlated in all stages of corpus luteum. The histogram values and plasma P$_4$ concentrations were positive correlated in developing, functional and pregnant corpora lutea, but negative correlated in regressing corpus luteum. Therefore, the measurement of corpus luteum area and histogram value by ultrasonography is reliable method for the assessment of luteal function, specially developing and regressing corpus luteum.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.958-964
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• 2010

Histogram Equalization(HE) is one of the well known methods for contrast enhancement. but, it did not applied directly due to side effects such as significant change in brightness or washed out appearance. Many conventional method try to overcome this problem but they did not guarantee various image or depend on user define parameter. In this paper, an Adaptive histogram Compensated Histogram Equalization(ACHE) is proposed for contrast enhancement. ACHE has a parameter that based on median of input image. Histogram of input image is compensated according to parameter. And then finally compensated histogram is equalized. Experimental results show that proposed method suppresses side effects such as detail loss or washed out appearance. Moreover, parameter calculated automatically with low computation complexity. As a result, it could applies FPD directly.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.102-107
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• 2015

In this paper, we propose a technique of drowsiness detection using a histogram for vehicle safety. The drowsiness of vehicle drivers is often the main cause of many vehicle accidents. Therefore, the checking of eye images in order to detect the drowsiness status of a driver is very important for preventing accidents. In our suggested method, we analyse the changes of a histogram of eye region images which are acquired using a CCD camera. We develop a drowsiness detection system using this histogram change information. The experimental results show that the proposed method enhances the accuracy of detecting drowsiness to nearly 97%, and can be used to prevent accidents due to driver drowsiness.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.111-118
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• 1996

A content-based image retrieval system is designed and implemetned using the color featurees which are histogram intersection and color pairs. The preprocessor for the image retrieval manage linearly the existing HSI(hue, saturation, saturation, intensity). Hue and intensity histogram thresholding for each color attribute is performed to split the chromatic and achromatic regions respectively. Grouping te indexes produced by the histogram intersection is used to save the retrieval times. Each image is divided into the cells of 32$\times$32 pixels, and color pairs are used to represent the query during retrievals. The recall/precision of histogram intersection is 0.621/0.663 and recall/precision of color pairs is 0.438/0.536. And recall/precision of proposed method is 0.765/0.775/. It is shown that the proposed method using histogram intersection and color pairs improves the retrieval rates.