• The KIPS Transactions:PartB
• /
• v.13B no.1 s.104
• /
• pp.53-62
• /
• 2006

Object recognition techniques using principal component analysis are disposed to be decreased recognition rate when lighting change of image happens. The purpose of this thesis is to propose an object recognition technique using new PCA analysis method that discriminates an object in database even in the case that the variation of illumination in training images exists. And the object recognition algorithm proposed here represents more enhanced recognition rate using improved k-Nearest Neighbor. In this thesis, we proposed an object recognition algorithm which creates object space by pre-processing and being learned image using histogram equalization and median filter. By spreading histogram of test image using histogram equalization, the effect to change of illumination is reduced. This method is stronger to change of illumination than basic PCA method and normalization, and almost removes effect of illumination, therefore almost maintains constant good recognition rate. And, it compares ingredient projected test image into object space with distance of representative value and recognizes after representative value of each object in model image is made. Each model images is used in recognition unit about some continual input image using improved k-Nearest Neighbor in this thesis because existing method have many errors about distance calculation.

• Journal of the Korea Computer Industry Society
• /
• v.7 no.5
• /
• pp.537-544
• /
• 2006

Image Search is one of the most exciting and fast growing research areas in the filed of multimedia technology. This paper conducts an empirical evaluation of color descriptor that uses the information of color distribution in color images, which is the most basic element for image search. With the experimental results, we observe that in the top 10% of precision, HSV, Daubechies 9/7 and 2 level decomposition have little better than others. Also histogram quadratic metrics outperform the Minkowski form distance metrics in similarity measurements, but spend more than 20 in computational times.

• The Journal of the Korea Contents Association
• /
• v.9 no.11
• /
• pp.225-230
• /
• 2009

Filtering has been used to improve the image quality not only in MRI but in most image processing fields. In this paper, modified Fermi-Direc filter was transformed in various shapes, and then the optimum shape was designed. In addition, Newly made filter was applied in real clinic, which showed the obvious improvement in image quality. In conclusion, filtered image was superior to original image in contrast and sharpness. Then, this was proved by the histogram of R, G, B channel used for the quantitative analysis.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2007.11a
• /
• pp.550-555
• /
• 2007

초음파 영상은 초음파 펄스를 이용하여 반사파를 수신하여 진단에 필요한 영상을 구성하는데 신호가 약해 질 경우 잡음이 발생하며 미세한 명암도 차이 등에 의해 분석과정에서 육안으로 인지하고 진단하는데 어려움이 있다. 특히 근골격계 검사를 위한 초음파 영상에서 근육 영역의 진단에 어려움을 준다. 따라서 본 논문에서는 초음파 영상에서 영상처리 기법을 이용하여 근육 영역을 검출할 수 있는 방법을 제안한다. 초음파 영상에서의 근육 영역검출은 피하지방층과 기타 영역 그리고 근육을 둘러싸고 있는 근육막 후보 영역을 검출한 후, 위치 정보와 형태학적 특징을 이용하여 최종적으로 근육막 내부 영역인 근육 영역을 검출한다. 제안된 방법의 근육막 후보 영역의 검출 과정은 개선된 히스토그램 스트레칭과 Mutiple연산으로 대비 차를 향상시키고 반복 이진화 기법을 적용한 후, 잡음에 의해 손실되거나 끊어진 근육막 영역을 거리 및 방향 분석을 이용하여 연결한 후에 근육막 후보 영역을 검출한다. 검출된 근육막 후보 영역의 형태학적 특징과 위치 정보를 이용하여 피하지방층과 기타 영역을 분류 한 후, 최종적으로 근육 영역을 검출한다. 실제 초음파 영상을 대상으로 제안된 근육 검출 방법을 적용하여 검출된 근육 영역과 전문의가 분석한 근육 영역을 비교한 결과, 제안된 근육 검출 방법이 전문의가 육안으로 분석한 근육영역과 근접하게 검출되어 본 논문에서 제안한 근육 영역 검출 방법이 효율적임을 확인할 수 있었다.

• The Journal of Korean Society for Radiation Therapy
• /
• v.19 no.2
• /
• pp.113-122
• /
• 2007

Purpose: We proposed the method using dose-volume Histogram index to compare prospective plan trials in tomotherapy planning optimization. Materials and Methods: For 3 patients in cranial region, thorax and abdominal region, we acquired computed tomography images with PQ 5000 in each case. Then we delineated target structure and normal organ contour with pinnacle Ver 7.6c, after transferred each data to tomotherapy planning system (hi-art system Ver 2.0), we optimized 3 plan trials in each case that used differ from beam width, pitch, importance. We analyzed 3 plan trials in each region with isodose distribution, dose-volume histogram and dose statistics. Also we verified 3 plan trials with specialized DVH-indexes that is dose homogeneity index in target organ, conformity index around target structure and dose gradient index in non-target structures. Results: We compared with the similarity of results that the one is decide the best plan trial using isodose distribution, dose volume histogram and dose statistics, and the another is using DVH-indexes. They all decided the same plan trial to better result in each case. Conclusion: In some of case, it was appeared a little difference of results that used to DVH-index for comparison of plan trial in tomotherapy by special goal in it. But because DVH-index represented both dose distribution in target structure and high dose risk about normal tissue, it will be reasonable method for comparison of many plan trials before the tomotherapy treatments.

• Journal of the Korea Convergence Society
• /
• v.8 no.5
• /
• pp.19-28
• /
• 2017

In this paper, we propose a method to reduce the difference in image characteristics when multiple camera images are captured for virtual space production. Sixty-four images were used by cross-mounting eight bodies and lenses, respectively. Image analysis compares and analyzes the standard deviation of the histogram and pixel distribution values. As a result of the analysis, it shows different image characteristics depending on the lens or image sensor, though it is a camera of the same model. In this paper, we have adjusted the distribution of the overall brightness value of the image to compensate for this difference. As a result, the average deviation was the maximum of (Indoor: 6.89, outdoor: 24.23), we obtained images with almost no deviation (Indoor: maximum 0.42, outdoor: maximum: 2.73). In the future, we will study and apply more accurate image analysis methods than image brightness distribution.

• The KIPS Transactions:PartB
• /
• v.19B no.2
• /
• pp.83-92
• /
• 2012

Multimedia contents can be copied and manipulated without quality degradation. Therefore, they are vulnerable to digital forgery and illegal distribution. In these days, with increasing the importance of multimedia security, various multimedia security techniques are studied. In this paper, we propose a content authentication algorithm based on reversible watermarking which supports JPEG compression commonly used for multimedia contents. After splitting image blocks, a specific authentication code for each block is extracted and embedded into the quantized coefficients on JPEG compression which are preserved against lossy processing. At a decoding process, the watermarked JPEG image is authenticated by extracting the embedded code and restored to have the original image quality. To evaluate the performance of the proposed algorithm, we analyzed image quality and compression ratio on various test images. The average PSNR value and compression ratio of the watermarked JPEG image were 33.13dB and 90.65%, respectively, whose difference with the standard JPEG compression were 2.44dB and 1.63%.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2005.11a
• /
• pp.213-216
• /
• 2005

자동차 번호판의 이미지에서 번호의 추출이나, 직물 이미지에서 오염 또는 훼손부분의 추출 또는 방사성 폐기물이나 기타 독극물 보관함의 이미지에서 오염이나 산화에 의한 훼손부위 등과 같은 목표물 이미지 추출은 흑백 이미지에서 명암의 차이를 이용하는 것보다는 컬러 이미지에서 색상의 차이를 이용하는 것이 더 효율적일 때가 많으며, 특히 배경과 목표물의 명암차이가 크지 않은 경우에 효과적이다. 배경과 목표물이 갖는 색상의 차이를 이용하여 분리하기 위해서 적색(R), 녹색(G), 청색(B) 의 RGB 평면 또는 순도(H), 포화도(S), 휘도(I)를 사용하는 HSI 컬러 평면 등이 많이 사용되며, 이 때 배경과 목표물의 색상의 히스토그램을 구해보면 보면 많은 경우 유사한 색 정보가 배경과 목표물에 공통으로 포함되어 분리에 어려움을 겪게 된다. 본 논문에서는 Fisher 선형 분리자(Fisher's linear discriminant)[1] 함수를 이용하여 3차원의 색상 특징 벡터를 1차원 직선에 투사하여 변환된 1차원 공간상에서 복잡성을 줄이고 효과적으로 분류할 수 있는 기법을 제안하였으며, 이를 도축된 식용 가금류의 영상에 적용하고 변질된 부분이 포함되어 식용으로 사용할 수 없는 것들을 효과적으로 분류할 수 있음을 보였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.3
• /
• pp.229-234
• /
• 2018

Texture is one of the most useful features in classifying and segmenting images. The LBP-based approach previously presented in the literature has been successful in many applications. However, it's theoretical foundation is based only on the difference of pixel values, and consequently it has a number of drawbacks like it performs poorly for the images corrupted with noise, and especially it cannot be used as a multiscale texture descriptor due to the exploding increase of feature vector dimension with increase of the number of neighbor pixels. In this paper, we present a method to address these drawbacks of LBP-based approach. More specifically, our approach quantizes the range of pixels values and construct a 3D histogram which captures the correlative information of pixels. This histogram is used as a texture feature. Several tests with texture images show that the proposed method outperforms the LBP-based approach in the problem of texture classification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.149-150
• /
• 2012

This paper presents a shot boundary detection method based on the global decision tree that allows for extraction of boundaries of high variations occurring due to camera breaks from frame difference values. For a start, difference values between frames are calculated through local X2-histogram and normalization. Next, the distances between difference values are calculated through normalization.