• Title/Summary/Keyword: Gray Level Image

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Tire tread pattern classification using gray level cooccurrence matrix for the binary image (이치화 영상에 대한 계조치 동시발생행렬을 이용한 타이어 접지 패턴의 분류)

  • 박귀태;김민기;김진헌;정순원
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.100-105
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    • 1992
  • Texture is one of the important characteristics that has been used to identify objects or regions of interest in an image. Tire tread patterns can be considered as a kind of texture, and these are classified with a texture analysis method. In this sense, this paper proposes a new algorithm for the classification of tire tread pattern. For the classification, cooccurrence matrix for the binary image is used. The performances are tested by experimentally 8 different tire tread pattern and the robustness is examined by including some kinds on noise.

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A new automatic white balance algorithm using non-linear gain (Non-linear gain을 적용한 Automatic White Balance기법)

  • Yun, Se-Hwan;Kim, Jin-Heon
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.27-29
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    • 2006
  • In this paper, we propose a new method of automatic white balance which is one of the image signal processing techniques. Our method is conceptually based on gray world assumption. However, while previous methods generate linear results as multiplying pixel values by a gain, our method generates non-linear results using the feature of B-Spline curves. The two merits of deriving non-linear results are preventing AWB failure from transforming strong color of high level into wrong color and well preserving original contrast of an input image.

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Spatial Contrast Enhancement using Local Statistics based on Genetic Algorithm

  • Choo, MoonWon
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.89-92
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    • 2017
  • This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

Optical security scheme using phase-encoded XOR operations (위상 변조 Exclusive-OR 연산을 이용한 광학적 암호화 방법)

  • 신창목;서동환;김수중
    • Korean Journal of Optics and Photonics
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    • v.14 no.6
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    • pp.623-629
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    • 2003
  • In this paper, we have proposed a full phase encryption scheme based on phase-encoded XOR operation. The proposed scheme encrypts a gray-level image by slicing an original image and combining with XORed images which resulted from phase-encoded XOR operations between sliced images and phase-encoded binary random images. Then we produce an encrypted image by combining only XORed images and a key image by only phase-encoded binary random images. The encrypted image and key image are converted into encrypted data and key data by a phase-encoding method. The merits are that the proposed encryption scheme can basically fulfill a high-level encryption using a full phase encryption scheme which has nonlinear and invisible characteristics. The scheme also improves security by encrypting the phase information before full phase encryption. The decryption system based on the principle of interference between a reference wave and a direct pixel-to-pixel mapping image of encrypted data with key data can be simply implemented using a phase-visualization system. Simulation results indicate that our proposed encryption scheme is effective and simple for a gray-scale image and optical decryption system.

Performance Test for the Long Distance Sprayer by an Image Processing (영상처리를 이용한 광역방제기 팬의 성능실험)

  • Min, B.R.;Kim, D.W.;Seo, K.W.;Hong, J.T.;Kim, W.;Choi, J.H.;Lee, D.W.
    • Journal of Animal Environmental Science
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    • v.14 no.3
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    • pp.159-166
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    • 2008
  • This research was carried out to test and analyze capacity of the long distance sprayer fan in large livestock farmhouses. Long distance sprayer was manufactured to be able to spray a lot of water, which was a solvent for agricultural chemicals and black dye with the maximum spraying distance of 140 m and the effective spraying distance of 100 m. The spraying quantity and the distance were measured the intensity values of images within A4 papers, which absorbed the agricultural chemicals by spraying by binary image processing. These A4 papers were fixed upon the height of 1 m from soil ground at regular 10 m interval. After the A4 papers were collected and analyzed the intensity values of gray level. Gray level was ranged from 0 to 255, where 0 was black and 255 was white. A4 paper was fallen down from the stick at 10 m distance, because there were too large amount of sprayed water with black dye. Also, the paper showed low gray level at distance 30 m because of dropping lots of black water. The intensity value of gray level was showed almost less than 200 on the A4 papers between the distance 20 m and 100 m, which meant equality of spraying quantity. Additionally, it was possible to spay agricultural chemicals of until 180 m. Throughout this research, long distance sprayer could apply for preventing hoof-and-mouth disease in large livestock farmhouses.

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A study of trabecular bone strength and morphometric analysis of bone microstructure from digital radiographic image (디지털방사선영상에서 추출한 해면질골의 강도와 미세구조의 형태계측학적 분석에 대한 연구)

  • Han Seung-Yun;Lee Sun-Bok;Oh Sung-Ook;Heo Min-Suk;Lee Sam-Sun;Choi Soon-Chul;Park Tae-Won;Kim Jong-Dae
    • Imaging Science in Dentistry
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    • v.33 no.2
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    • pp.113-119
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    • 2003
  • Purpose : To evaluate the relationship between morphometric analysis of bone microstructure from digital radiographic image and trabecular bone strength. Materials and Methods : One hundred eleven bone specimens with 5 mm thickness were obtained from the mandibles of 5 pigs. Digital images of specimens were taken using a direct digital intraoral radiographic system. After selection of ROI (100 × 100 pixel) within the trabecular bone, mean gray level and standard deviation were obtained. Fractal dimension and the variants of morphometric analysis (trabecular area, periphery, length of skeletonized trabeculae, number of terminal point, number of branch point) were obtained from ROI. Punch sheer strength analysis was performed using Instron (model 4465, Instron Corp., USA). The loading force (loading speed 1 mm/min) was applied to ROI of bone specimen by a 2 mm diameter punch. Stress-deformation curve was obtained from the punch sheer strength analysis and maximum stress, yield stress, Young's modulus were measured. Results: Maximum stress had a negative linear correlation with mean gray level and fractal dimension significantly (p<0.05). Yield stress had a negative linear correlation with mean gray level, periphery, fractal dimension and the length of skeletonized trabeculae significantly (p < 0.05). Young's modulus had a negative linear correlation with mean gray level and fractal dimension significantly (p < 0.05). Conclusions : The strength of cancellous bone exhibited a significantly linear relationship between mean gray level, fractal dimension and morphometric analysis. The methods described above can be easily used to evaluate bone quality clinically.

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Heterogeneous Face Recognition Using Texture feature descriptors (텍스처 기술자들을 이용한 이질적 얼굴 인식 시스템)

  • Bae, Han Byeol;Lee, Sangyoun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.3
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    • pp.208-214
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    • 2021
  • Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

A Study on Improved Codeword Extraction for Decoder of Two Dimensional Barcode PDF417 (PDF417 이차원 바코드 디코더에서 코드워드 추출 알고리즘의 성능 개선에 관한 연구)

  • 정정구;한희일
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.89-92
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    • 2002
  • In this paper we present a barcode reader to decode two-dimensional symbology PDF-417 and propose a novel method to extract the bar-space patterns directly from the gray-level barcode image, which employs the location and the distance between extreme points of each row of the barcode image. This algorithm proves to be very robust from the high convolution distortion environments such as defocussing and warping, even under badly illuminating condition. If the scanned barcode image is a result of the convolution of a Gaussian-shaped point spread function with a bi-level image, popular image segmentation methods such as image thresholding can not distinguish between very narrow bar-space patterns with a couple of pixels wide. The proposed algorithm shows improved performance over current barcode readers.

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Optical security system using multi-phase separation and phase-wrapping method (다중 위상 분할과 위상 랩핑 방법을 이용한 광 암호화 시스템)

  • Shin Chang Mok;Kim Soo Joong;Seo Dong Hoan
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.42 no.6 s.336
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    • pp.31-38
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    • 2005
  • In this paper, we proposed an optical security system based on a gray-image exclusive-OR encryption using multi-phase separation and phase-wrapping method. For encryption, a gray image is sliced into binary images, which have the same pixel value, and these images are encrypted by modified XOR rules with binary random images. The XORed images and the binary images respectively combined and converted into full phase images, called an encrypted image and a key image. For decryption, when the encrypted image and key image are used as inputs on optical elements, Practically due to limited controllability of phase range in optical elements, the original gray image cannot be efficiently reconstructed by these optical elements. Therefore, by decreasing the phase ranges of the encrypted image and key image using a phase-wrapping method and separating these images into low-level phase images using multi-phase separation, the gray image can be reconstructed by optical elements which have limited control range. The decrytion process is simply implemented by interfering a multiplication result of encrypted image and key image with reference light. The validity of proposed scheme is verified and the effects, which are caused by phase limitation in decryption process, is analyzed by using computer simulations.

Melanoma Classification Algorithm using Gray-level Conversion Matrix Feature and Support Vector Machine (회색도 변환 행렬 특징과 SVM을 이용한 흑색종 분류 알고리즘)

  • Koo, Jung Mo;Na, Sung Dae;Cho, Jin-Ho;Kim, Myoung Nam
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.130-137
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    • 2018
  • Recently, human life is getting longer due to change of living environment and development of medical technology, and silver medical technology has been in the limelight. Geriatric skin disease is difficult to detect early, and when it is missed, it becomes a malignant disease and is difficult to treatment. Melanoma is one of the most common diseases of geriatric skin disease and initially has a similar modality with the nevus. In order to overcome this problem, we attempted to perform a feature analysis in order to attempt automatic detection of melanoma-like lesions. In this paper, one is first order analysis using information of pixels in radiomic feature. The other is a gray-level co-occurrence matrix and a gray level run length matrix, which are feature extraction methods for converting image information into a matrix. The features were extracted through these analyses. And classification is implemented by SVM.