• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.173-185
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• 2009

This paper proposes two new image contrast enhancement methods, RSWHE (Recursively Separated and Weighted Histogram Equalization) and RSWHS (Recursively Separated and Weighted Histogram Specification). RSWHE is a histogram equalization method based on histogram decomposition and weighting, whereas RSWHS is a histogram specification method based on histogram decomposition and weighting. The two proposed methods work as follows: 1) decompose an input histogram based on the image's mean brightness, 2) compute the probability for the area corresponding to each sub-histogram, 3) modify the sub-histogram by weighting it with the computed probability value, 4) lastly, perform histogram equalization (in the case of RSWHE) or histogram specification (in the case of RSWHS) on the modified sub-histograms independently. Experimental results show that RSWHE and RSWHS outperform other methods in terms of contrast enhancement and mean brightness preservation as well.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.856-860
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• 2009

Wang and Ward developed an image contrast enhancement method called WTHE (Weighted and Thresholded Histogram Equalization). In this paper, we propose an improved variant of WTHE called DWTHE(Decomposable WTHE) that enhances WTHE through the use of histogram decomposition. Specifically, DWTHE divides an input histogram by using image's mean brightness or equally-spaced brightness points, computes a probability value for each sub-histogram, modifies the sub-histograms by using those probability values as weights, and then performs histogram equalization on the modified input histogram. As opposed to WTHE that uses a single weight, DWTHE uses multiple weights derived from histogram decomposition. Experimental results show that the proposed method outperforms the previous histogram equalization based methods.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.364-366
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• 2005

From the 90's, the image information retrieval methods have been on progress. As good examples of the methods, Conventional histogram method and merged-color histogram method were introduced. They could get good result in image retrieval. However, Conventional histogram method has disadvantages if the histogram is shifted as a result of intensity change. Merged-color histogram, also, causes more process so, it needs more time to retrieve images. In this paper, we propose an improved new method using Adaptive Color Histogram Bin Matching(AHB) in image retrieval. The proposed method has been tested and verified through a number of simulations using hundreds of images in a database. The simulation results have Quickly yielded the highly accurate candidate images in comparison to other retrieval methods. We show that AHB's can give superior results to color histograms for image retrieval.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.657-662
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• 2014

Usually, spatial information can be incorporated into histograms by taking histograms of a multiresolution image. For these reasons, many researchers are interested in multiresolution histogram processing. If the relation and sensitivity of the multiresolution images are well combined without loss of information, we can obtain satisfactory results in several fields of image processing including histogram equalization, specification and pattern matching. In this paper, we propose a multiresolution histogram specification method that improves the accuracy of histogram specification. The multiresolution decomposition technique is used in order to overcome the unique feature of a histogram specification affected by a quantization error of a digitalized image. The histogram specification is processed after the reduction of image resolution in order to enhance the accuracy of the results by histogram specification methods. The experimental results show that the proposed method enhances the accuracy of specification compared to conventional methods.

• Convergence Security Journal
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• v.7 no.1
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• pp.107-113
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• 2007

This paper proposes the shifted histogram method (SHM), for histogram-based image retrieval based on the dominant colors in images. The histogram-based method is very suitable for color image retrieval because retrievals are unaffected by geometrical changes in images, such as translation and rotation. Images with the same visual information, but with shifted color intensity, may significantly degrade if the conventional histogram intersection method (HIM) is used. To solve this problem, we use the shifted histogram method (SHM). Our experimental results show that the shifted histogram method has significant higher retrieval performance than the standard histogram method.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.668-676
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• 2017

Recently, the importance of big data has been emphasized with the development of smartphone, web/SNS. As a result, MapReduce, which can efficiently process big data, is receiving worldwide attention because of its excellent scalability and stability. Since big data has a large amount, fast creation speed, and various properties, it is more efficient to process big data summary information than big data itself. Wavelet histogram, which is a typical data summary information generation technique, can generate optimal data summary information that does not cause loss of information of original data. Therefore, a system applying a wavelet histogram generation technique based on MapReduce has been actively studied. However, existing research has a disadvantage in that the generation speed is slow because the wavelet histogram is generated through one or more MapReduce Jobs. And there is a high possibility that the error of the data restored by the wavelet histogram becomes large. However, since the wavelet histogram generation system based on the MapReduce developed in this paper generates the wavelet histogram through one MapReduce Job, the generation speed can be greatly increased. In addition, since the wavelet histogram is generated by adjusting the error boundary specified by the user, the error of the restored data can be adjusted from the wavelet histogram. Finally, we verified the efficiency of the wavelet histogram generation system developed in this paper through performance evaluation.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.959-968
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• 2005

The piecewise linear histogram can be used as a simple and efficient tool for the density estimator. But, this piecewise linear histogram is discontinuous function. We suppose the piecewise continuous linear histogram as a simple and efficient tool for the density estimator and the alternative of the piecewise linear histogram.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.517-521
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• 2008

Hand motion classification problem is considered as basis for sign or gesture recognition. We promote optical flow as main feature extracted from images sequences to simultaneously segment the motion's area by its magnitude and characterize the motion' s directions by its orientation. We manage the flow orientation histogram as motion descriptor. A motion is encoded by concatenating the flow orientation histogram from several frames. We utilize simple histogram matching to classify the motion sequences. Attempted experiments show the feasibility of our method for hand motion localization and classification.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.193-198
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• 2010

In this paper, an efficient contrast enhancement algorithm using histogram stretching is proposed. Histogram equalization (HE) and histogram stretching (HS) are effective techniques for contrast enhancement. However, HE and HS result often in excessive contrast enhancement. Proposed technique not only produces better results than those of conventional contrast enhancement techniques, but is also adaptively adjusted to image contents.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.317-320
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• 2002

In this paper, an automatic histogram specification method is proposed for image enhancement, Fuzzy membership value is adopted for the representation of image histogram. The desired PDF is automatically constructed by the fuzzy membership value. Fuzzy membership value is extracted from dark membership, bright membership function and original histogram. The effectual results are demonstrated by desired PDF which meet the image enhancement requirements. The performance and effectiveness are shown by the analysis and the resultant image in comparison with histogram equalization method.