• Title/Summary/Keyword: Bit-Sliced Image

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Real-time 2-D Separable Median Filter (실시간 2차원 Separable 메디안 필터)

  • Jae Gil Jeong
    • Journal of the Korea Computer Industry Society
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    • v.3 no.3
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    • pp.321-330
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    • 2002
  • A 2-D median filter has many applications in various image and video signal processing areas. The rapid development in VLSI technology makes it possible to implement a real-time or near real-time 2-D median filter with reasonable cost. For the efficient VLSI implementation, the algorithm should have characteristics such as small memory requirements, regular computations, and local data transfers. This paper presents an architecture of the real-time two-dimensional separable median filter which has appropriate characteristics for the VLSI implementation. For the efficient two-dimensional median filter, a separable two-dimensional median filtering structure and a bit-sliced pipelined median searching algorithm are used. A behavioral simulator is implemented with C language and used for the analysis of the presented architecture.

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Texture Descriptor Using Correlation of Quantized Pixel Values on Intensity Range (화소값의 구간별 양자화 값 상관관계를 이용한 텍스춰 기술자)

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