• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.4
• /
• pp.474-477
• /
• 1999

In this paper, a new method of measuring of distance between digital images, the 2D Integra-Normalizer, is proposed and compared with the grey block distance (GBD) to show its superiority of images. The 2D Integra-Normalizer removes a restriction that the image to be compared is {{{{ { 2}^{n } }}}} dimension where n is a positive integer, which means that any dimensional image can be applied to the 2D Integra-Normalizer for measuring distance of images. In addition, the 2D Integra-Normalizer measures the distance of images more in detail than the GBD with a better interpretation that is more close to human's intuitive understanding.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.50 no.7
• /
• pp.350-353
• /
• 2001

In general, the Least Square Error method is used for signal classification to measure distance in the $l^2$ metric or the $L^2$ metric space. A defect of the Least Square Error method is that it does not classify properly some waveforms, which is due to the property of the Least Square Error method: the global analysis. This paper proposes a new linear operator, the Integra-Normalizer, that removes the problem. The Integra-Normalizer possesses excellent property that measures the degree of relative similarity between signals by expanding the functional space with removing the restriction on the functional space inherited by the Least Square Error method. The Integra-Normalizer shows superiority to the Least Square Error method in measuring the relative similarity among one dimensional waveforms.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.8
• /
• pp.491-494
• /
• 2000

A scheme is proposed for measuring similarities between the binary pulse signals in the pulse-code modulation using the Integra-Normalizer. The Integra-Normalizer provides a better interpretation of the relationship between the pulse signals by removing redundant codes, which maps all possible observed signals to one of the codes to be received with relative similarities between each pair of compared signals. The proposed method provides better error tolerance than L2 metric, such as Hamming distance, since the distances between pulse signals are measured not useful for the time-delay detection in the pulse-code modulation.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2933-2935
• /
• 2000

본 논문에서는, $L^2$ 메트릭(Metric)을 사용한 신호간의 거리 측정 방법의 약점을 보완하기 위해 연구된 인테그라-노말라이저(Integra-Normalizeer)를 사용함에 있어, 웨이브렛(Wavelets)의 멀타이레졸루션(Multiresolution)의 특성을 이용, 신호간의 거리 측정뿐만이 아니라, 신호간의 다른 점이 어느 주파수 영역에 존재하나 하는 정보도 획득할 수 있게 하였다.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.3
• /
• pp.342-349
• /
• 1999

The metric defined on the domain deformation space better measures the similarity between bounded and continuous signals for the purpose of classification via the metric distances between signals. In this paper, a modified domain deformation theory is introduced for one-dimensional signal classification. A new metric defined on a modified domain deformation for measuring the distance between signals is employed. By introducing a newly defined metric space via the newly defined Integra-Normalizer, the assumption that domain deformation is applicable only to continuous signals is removed such that any kind of integrable signal can be classified. The metric on the modified domain deformation has an advantage over the $L^2$ metric as well as the previously introduced domain deformation does.