http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
허경무(Kyung Moo Huh) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.2
The histogram specification turns the shape of a histogram into that we want to specify. This technique can be applied usefully in various image processing fields such as machine vision. However, the histogram specification technique has its basic limits. For instance, the histogram does not have location information of pixels. Also, the accuracy of the specification drops because of quantization errors of the digitized image. In this paper, we proposed a multiresolution histogram specification method in order to improve the accuracy of specification in terms of resemblance between destination and source image. The experimental results show that the proposed method enhances the accuracy of the specification compared to the conventional methods.
이미지 향상을 위해 공간영역에서 다중해상도를 이용한 개선된 히스토그램 특정화 방법
허경무(Kyung-Moo Huh) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.6
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.
허경무(Kyung Moo Huh) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.5
Generally, feature area detection methods are widely used for face expression recognition by detecting the feature areas of human eyes, eyebrows and mouth. In this paper, we proposed a face expression recognition method using the histograms of the face, eyes and mouth for many applications including robot technology. The experimental results show that the proposed method has a new type of face expression recognition capability compared to conventional methods.