• Title/Summary/Keyword: Local Histogram

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Cut Detection Algorithm Using the Characteristic Of Wavelet Coefficients in Each Subband (대역별 웨이블릿 계수특성을 이용한 장면전환점 검출기법)

  • Moon Young ho;No Jung Jin;Yoo Ji sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.10C
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    • pp.1414-1424
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    • 2004
  • In this paper, an algorithm using wavelet transform for detecting a cut that is a radical scene transition point, and fade and dissolve that are gradual scene transition points is proposed. The conventional methods using wavelet transform for this purpose is using features in both spatial and frequency domain. But in the proposed algorithm, the color space of an input image is converted to YUV and then luminance component Y is transformed in frequency domain using 2-level lifting. Then, the histogram of only low frequency subband that may contain some spatial domain features is compared with the previous one. Edges obtained from other higher bands can be divided into global, semi-global and local regions and the histogram of each edge region is compared. The experimental results show the performance improvement of about 17% in recall and 18% in precision and also show a good performance in fade and dissolve detection.

Extraction of an Effective Saliency Map for Stereoscopic Images using Texture Information and Color Contrast (색상 대비와 텍스처 정보를 이용한 효과적인 스테레오 영상 중요도 맵 추출)

  • Kim, Seong-Hyun;Kang, Hang-Bong
    • Journal of Korea Multimedia Society
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    • v.18 no.9
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    • pp.1008-1018
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    • 2015
  • In this paper, we propose a method that constructs a saliency map in which important regions are accurately specified and the colors of the regions are less influenced by the similar surrounding colors. Our method utilizes LBP(Local Binary Pattern) histogram information to compare and analyze texture information of surrounding regions in order to reduce the effect of color information. We extract the saliency of stereoscopic images by integrating a 2D saliency map with depth information of stereoscopic images. We then measure the distance between two different sizes of the LBP histograms that are generated from pixels. The distance we measure is texture difference between the surrounding regions. We then assign a saliency value according to the distance in LBP histogram. To evaluate our experimental results, we measure the F-measure compared to ground-truth by thresholding a saliency map at 0.8. The average F-Measure is 0.65 and our experimental results show improved performance in comparison with existing other saliency map extraction methods.

Content-based Image Retrieval System (내용기반 영상검색 시스템)

  • Yoo, Hun-Woo;Jang, Dong-Sik;Jung, She-Hwan;Park, Jin-Hyung;Song, Kwang-Seop
    • Journal of Korean Institute of Industrial Engineers
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    • v.26 no.4
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    • pp.363-375
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    • 2000
  • In this paper we propose a content-based image retrieval method that can search large image databases efficiently by color, texture, and shape content. Quantized RGB histograms and the dominant triple (hue, saturation, and value), which are extracted from quantized HSV joint histogram in the local image region, are used for representing global/local color information in the image. Entropy and maximum entry from co-occurrence matrices are used for texture information and edge angle histogram is used for representing shape information. Relevance feedback approach, which has coupled proposed features, is used for obtaining better retrieval accuracy. Simulation results illustrate the above method provides 77.5 percent precision rate without relevance feedback and increased precision rate using relevance feedback for overall queries. We also present a new indexing method that supports fast retrieval in large image databases. Tree structures constructed by k-means algorithm, along with the idea of triangle inequality, eliminate candidate images for similarity calculation between query image and each database image. We find that the proposed method reduces calculation up to average 92.9 percent of the images from direct comparison.

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Reversible Data Embedding Algorithm based on Pixel Value Prediction Scheme using Local Similarity in Image (지역적 유사성을 이용한 픽셀 값 예측 기법에 기초한 가역 데이터 은닉 알고리즘)

  • Jung, Soo-Mok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.6
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    • pp.617-625
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    • 2017
  • In this paper, an effective reversible data embedding algorithm was proposed to embed secrete data into image. In the proposed algorithm, prediction image is generated by accurately predicting pixel values using local similarity existing in image, difference sequence is generated using the generated prediction image and original cover image, and then histogram shift technique is applied to create a stego-image with secrete data hidden. Applying the proposed algorithm, secrete data can be extracted from the stego-image and the original cover image can be restored without loss. Experimental results show that it is possible to embed more secrete data into cover image than APD algorithm by applying the proposed algorithm.

New Approach to Two-wheeler Detection using Correlation Coefficient based on Histogram of Oriented Gradients

  • Lee, Yeunghak;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.3 no.4
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    • pp.119-128
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    • 2016
  • This study aims to suggest a new algorithm for detecting two-wheelers on road that have various shapes according to the viewing angle for vision based intelligent vehicles. This article describes a new approach to two-wheelers detection algorithm riding on people based on modified Histogram of Oriented Gradients (HOG) using correlation coefficient (CC). The CC between two local area variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using HOG which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the CC between the area of each cell and one of two-wheelers, can be extracted as the weighting factor in process for normalizing the modified HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

Comparison of Image Duplication Detection Using the Polar Coordinates System and Histogram of Oriented Gradients Methods

  • Gunadi, Kartika;Adipranata, Rudy;Suryajaya, Ivan
    • Journal of information and communication convergence engineering
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    • v.17 no.1
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    • pp.67-73
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    • 2019
  • In the current era of digital technology, and with the help of existing software, digital photo manipulation is becoming easier and faster. One example of this is the development of powerful image processing software that makes it easy for a digital image to be manipulated and edited. It is therefore very important to protect and maintain public trust in digital images. Several methods have been developed to detect image manipulation. In this paper, we compare two methods for detecting image duplication due to copy-move actions, namely the polar coordinate system and the histogram of oriented gradients methods. The former is a method based on the transfer of a Cartesian image to a polar form, making it easy to tell whether there are objects that have undergone a copy/move in an image, while the latter is a method for retrieving information related to the distribution, which uses a target in the local area as a tool to represent the shape of the target. We compare the accuracy, speed and memory usage of these two methods.

Adaptive Bayesian Object Tracking with Histograms of Dense Local Image Descriptors

  • Kim, Minyoung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.104-110
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    • 2016
  • Dense local image descriptors like SIFT are fruitful for capturing salient information about image, shown to be successful in various image-related tasks when formed in bag-of-words representation (i.e., histograms). In this paper we consider to utilize these dense local descriptors in the object tracking problem. A notable aspect of our tracker is that instead of adopting a point estimate for the target model, we account for uncertainty in data noise and model incompleteness by maintaining a distribution over plausible candidate models within the Bayesian framework. The target model is also updated adaptively by the principled Bayesian posterior inference, which admits a closed form within our Dirichlet prior modeling. With empirical evaluations on some video datasets, the proposed method is shown to yield more accurate tracking than baseline histogram-based trackers with the same types of features, often being superior to the appearance-based (visual) trackers.

Projected Local Binary Pattern based Two-Wheelers Detection using Adaboost Algorithm

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.1 no.2
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    • pp.119-126
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    • 2014
  • We propose a bicycle detection system riding on people based on modified projected local binary pattern(PLBP) for vision based intelligent vehicles. Projection method has robustness for rotation invariant and reducing dimensionality for original image. The features of Local binary pattern(LBP) are fast to compute and simple to implement for object recognition and texture classification area. Moreover, We use uniform pattern to remove the noise. This paper suggests that modified LBP method and projection vector having different weighting values according to the local shape and area in the image. Also our system maintains the simplicity of evaluation of traditional formulation while being more discriminative. Our experimental results show that a bicycle and motorcycle riding on people detection system based on proposed PLBP features achieve higher detection accuracy rate than traditional features.

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Regional Contrast Enhancement for Local Dimming Backlight on Small-sized Mobile Display

  • Chung, Jin-Young;Kim, Ki-Doo
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.972-974
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    • 2009
  • This paper presents smart regional contrast enhancement technique of partitioned image for local dimming backlight on small-sized mobile display to reach two goals. One is to save the power consumption, and the other to improve contrast ratio of display image. Recently new advanced method is proposed, named local dimming method, that backlight LED is positioned on backside of the display panel. So it is important to partition an image by sub blocks and then post-processing independantly. This means regional contrast enhancement. After partitioning, we compare the mean luminance(Y) value of each sub-block image with the one of original whole image. If some blocks have the mean value lower than the one of whole image, they are processed with the proposed method and others are bypassed. Simultaneously the information of the processed blocks are transferred to BLC(Backlight LED Controller). And then the supply current of each backlight LED is reduced to realize the contrast ratio enhancement and at the same time to power consumption reduction. In addition, we verify this proposed method is free from blocking artifacts.

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Parametric study on probabilistic local seismic demand of IBBC connection using finite element reliability method

  • Taherinasab, Mohammad;Aghakouchak, Ali A.
    • Steel and Composite Structures
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    • v.37 no.2
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    • pp.151-173
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    • 2020
  • This paper aims to probabilistically evaluate performance of two types of I beam to box column (IBBC) connection. With the objective of considering the variability of seismic loading demand, statistical features of the inter-story drift ratio corresponding to the second, fifth and eleventh story of a 12-story steel special moment resisting frames are extracted through incremental dynamic analysis at global collapse state. Variability of geometrical variables and material strength are also taken into account. All of these random variables are exported as inputs to a probabilistic finite element model which simulates the connection. At the end, cumulative distribution functions of local seismic demand for each component of each connection are provided using histogram sampling. Through a parametric study on probabilistic local seismic demand, the influence of some geometrical random variables on the performance of IBBC connections is demonstrated. Furthermore, the probabilistic study revealed that IBBC connection with widened flange has a better performance than the un-widened flange. Also, a design procedure is proposed for WF connections to achieve a same connection performance in different stories.