• Title/Summary/Keyword: DCT-Based Features

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A Discontinuity feature Enhancement Filter Using DCT fuzziness (DCT블록의 애매성을 이용한 불연속특징 향상 필터)

  • Kim, Tae-Yong
    • Journal of Korea Multimedia Society
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    • v.8 no.8
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    • pp.1069-1079
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    • 2005
  • Though there have been many methods to detect features in spatial domain, in the case of a compressed image it has to be decoded, processed and encoded again. Alternatively, we can manipulate a compressed image directly in the Discrete Cosine Transform (DCT) domain that has been used for compressing videos or images in the standards like MPEG and JPEG. In our previous work we proposed a model-based discontinuity evaluation technique in the DCT domain that had problems in the rotated or non-ideal discontinuities. In this paper, we propose a fuzzy filtering technique that consists of height fuzzification, direction fuzzification, and forty filtering of discontinuities. The enhancement achieved by the fuzzy tittering includes the linking, thinning, and smoothing of discontinuities in the DCT domain. Although the detected discontinuities are rough in a low-resolution image for the size (8${\times}$8 pixels) of the DCT block, experimental results show that this technique is fast and stable to enhance the qualify of discontinuities.

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2D Adjacency Matrix Generation using DCT for UWV Contents (DCT를 통한 UWV 콘텐츠의 2D 인접도 행렬 생성)

  • Xiaorui, Li;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.22 no.3
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    • pp.366-374
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    • 2017
  • Since a display device such as TV or digital signage is getting larger, the types of media is getting changed into wider view one such as UHD, panoramic and jigsaw-like media. Especially, panoramic and jigsaw-like media is realized by stitching video clips, which are captured by different camera or devices. However, a stitching process takes long time, and has difficulties in applying for a real-time process. Thus, this paper suggests to find out 2D Adjacency Matrix, which tells spatial relationships among those video clips in order to decrease a stitching processing time. Using the Discrete Cosine Transform (DCT), we convert the each frame of video source from the spatial domain (2D) into frequency domain. Based on the aforementioned features, 2D Adjacency Matrix of images could be found that we can efficiently make the spatial map of the images by using DCT. This paper proposes a new method of generating 2D adjacency matrix by using DCT for producing a panoramic and jigsaw-like media through various individual video clips.

A adaptively robust method of DCT-based watermarking (DCT 기반 워터마킹의 적응적 강인화 방법)

  • Jun, Young-Min;Kim, Gye-Young;Choi, Hyung-Il
    • The KIPS Transactions:PartB
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    • v.10B no.6
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    • pp.629-638
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    • 2003
  • In this paper, we propose an improved method of watermarking to increase the invisibility of a watermark and robustness against attacks for the purpose of removing the embedded watermark. The proposed method adaptively selects DCT blocks and determines position and intensity for watermarking based on the characteristics of human visual system. The used features are texture, luminance and contrast. We show the experimental results against image processing attacks such as cropping, image enhancement, low pass filtering, and JPEG compression, and then discuss the performance of the proposed method.

A GCST-based Digital Image Watermarking Scheme (GCST 기반 디지털 영상 워터마킹 방법)

  • Lee, Juck-Sik
    • Journal of the Institute of Convergence Signal Processing
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    • v.13 no.3
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    • pp.142-149
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    • 2012
  • Various image transformations can be used to compress images, to reduce noises in images and to extract useful features. Watermarking techniques using DCT and DWT have been a lot of research interest in the spread of multimedia contents. In this paper, Gabor cosine and sine transform considered as human visual filter is applied to embedding and extraction of watermarks for digital images. The proposed transform is used for watermarking with fifteen attacks. Randomly normal distributed noises are used as an embedded watermark. To measure the similarity between the embedded watermark and extracted one, a correlation value is computed and furthermore is compared with that of existing DCT method. Correlation values of extracted watermark are computed with randomly normal distributed noise sequences, and the sequence with the largest correlation value is declared as the embedded watermark. Frequency components are divided into various bands. Experimental results for low frequency and mid-frequency bands have shown that the proposed GCST provides a good watermarking algorithm and its performance is better than DCT.

A Image Search Algorithm using Coefficients of The Cosine Transform (여현변환 계수를 이용한 이미지 탐색 알고리즘)

  • Lee, Seok-Han
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.1
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    • pp.13-21
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    • 2019
  • The content based on image retrieval makes use of features of information within image such as color, texture and share for Retrieval data. we present a novel approach for improving retrieval accuracy based on DCT Filter-Bank. First, we perform DCT on a given image, and generate a Filter-Bank using the DCT coefficients for each color channel. In this step, DC and the limited number of AC coefficients are used. Next, a feature vector is obtained from the histogram of the quantized DC coefficients. Then, AC coefficients in the Filter-Bank are separated into three main groups indicating horizontal, vertical, and diagonal edge directions, respectively, according to their spatial-frequency properties. Each directional group creates its histogram after employing Otsu binarization technique. Finally, we project each histogram on the horizontal and vertical axes, and generate a feature vector for each group. The computed DC and AC feature vectors bins are concatenated, and it is used in the similarity checking procedure. We experimented using 1,000 databases, and as a result, this approach outperformed the old retrieval method which used color information.

Image Compression Using DCT Map FSVQ and Single - side Distribution Huffman Tree (DCT 맵 FSVQ와 단방향 분포 허프만 트리를 이용한 영상 압축)

  • Cho, Seong-Hwan
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.10
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    • pp.2615-2628
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    • 1997
  • In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

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Efficient Content-Based Image Retrieval Methods Using Color and Texture

  • Lee, Sang-Mi;Bae, Hee-Jung;Jung, Sung-Hwan
    • ETRI Journal
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    • v.20 no.3
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    • pp.272-283
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    • 1998
  • In this paper, we propose efficient content-based image retrieval methods using the automatic extraction of the low-level visual features as image content. Two new feature extraction methods are presented. The first one os an advanced color feature extraction derived from the modification of Stricker's method. The second one is a texture feature extraction using some DCT coefficients which represent some dominant directions and gray level variations of the image. In the experiment with an image database of 200 natural images, the proposed methods show higher performance than other methods. They can be combined into an efficient hierarchical retrieval method.

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Digital Watermark Based Error Detection for MPEG-4 Bitstream Error

  • Hiroyuki Okada;Shiitev, Altan-Erdene;Song, Hak-Sop;Gen Fujita;Takao Onoye;Isao Shirakawa
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.152-155
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    • 2002
  • In this paper, a new approach is proposed for the error detection dedicated to MPEG-4 video coding by using the digital watermarking. In the process of encoding, the proposed scheme abstracts the macroblock features of headers, motion vectors, and Discrete Cosine Transform (DCT) coefficients, which are embedded in the quantized DCT coefficients as the digital watermarks. The decoder performs the accurate error detection through the watermark extraction. Simulation results demonstrate that the error detection ability of the proposed approach can be significantly enhanced, and that digital watermark embedding incurs little degradation to the picture quality.

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Automatic Colorectal Polyp Detection in Colonoscopy Video Frames

  • Geetha, K;Rajan, C
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.11
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    • pp.4869-4873
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    • 2016
  • Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. Histograms of binary patterns computed across regions are used to describe textures. Every pixel is contrasted relative to gray levels of neighbourhood pixels. In this study, colorectal polyp detection was performed with colonoscopy video frames, with classification via J48 and Fuzzy. Features such as color, discrete cosine transform (DCT) and LBP were used in confirming the superiority of the proposed method in colorectal polyp detection. The performance was better than with other current methods.

Selective Feature Extraction Method Between Markov Transition Probability and Co-occurrence Probability for Image Splicing Detection (접합 영상 검출을 위한 마르코프 천이 확률 및 동시발생 확률에 대한 선택적 특징 추출 방법)

  • Han, Jong-Goo;Eom, Il-Kyu;Moon, Yong-Ho;Ha, Seok-Wun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.4
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    • pp.833-839
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    • 2016
  • In this paper, we propose a selective feature extraction algorithm between Markov transition probability and co-occurrence probability for an effective image splicing detection. The Features used in our method are composed of the difference values between DCT coefficients in the adjacent blocks and the value of Kullback-Leibler divergence(KLD) is calculated to evaluate the differences between the distribution of original image features and spliced image features. KLD value is an efficient measure for selecting Markov feature or Co-occurrence feature because KLD shows non-similarity of the two distributions. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. To verify our algorithm we used grid search and 6-folds cross-validation. Based on the experimental results it shows that the proposed method has good detection performance with a limited number of features compared to conventional methods.