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Machine Learning in Image Processing

  1. Given blurred observations of a stationary scene captured using a static camera but with different and unknown light source positions, we estimate the light source positions and scene structure (surface gradie...

    Authors: Swati Sharma and Manjunath V. Joshi
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:785364
  2. A new method for image compression based on morphological associative memories (MAMs) is presented. We used the MAM to implement a new image transform and applied it at the transformation stage of image coding...

    Authors: Enrique Guzmán, Oleksiy Pogrebnyak, Cornelio Yañez and Luis Pastor Sanchez Fernandez
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:426580
  3. The development of an efficient adaptively accelerated iterative deblurring algorithm based on Bayesian statistical concept has been reported. Entropy of an image has been used as a "prior" distribution and in...

    Authors: Manoj Kumar Singh, Uma Shanker Tiwary and Yong-Hoon Kim
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:674038
  4. A framework for the unification of statistical and structural information for pattern retrieval based on local feature sets is pre-sented. We use local features constructed from coefficients of quantized block...

    Authors: Daidi Zhong and Irek Defée
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:631297
  5. Learning how to extract texture features from noncontrolled environments characterized by distorted images is a still-open task. By using a new rotation-invariant and scale-invariant image descriptor based on ...

    Authors: Javier A. Montoya-Zegarra, João Paulo Papa, Neucimar J. Leite, Ricardo da Silva Torres and Alexandre Falcão
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:691924
  6. Manifold learning may be seen as a procedure aiming at capturing the degrees of freedom and structure characterizing a set of high-dimensional data, such as images or patterns. The usual goals are data underst...

    Authors: M. Brucher, Ch. Heinrich, F. Heitz and J.-P. Armspach
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:862015
  7. The development of very high-resolution (VHR) satellite imagery has produced a huge amount of data. The multiplication of satellites which embed different types of sensors provides a lot of heterogeneous image...

    Authors: Germain Forestier, Cédric Wemmert and Pierre Gançarski
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:374095
  8. We propose a new method to optimize the completely-trained boosted cascade detector on an enforced training set. Recently, due to the accuracy and real-time characteristics of boosted cascade detectors like th...

    Authors: Dong Woo Park and Kyoung Mu Lee
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:183804
  9. Subspace methods have been successfully applied to face recognition tasks. In this study we propose a face recognition algorithm based on a linear subspace projection. The subspace is found via utilizing a var...

    Authors: Moshe Butman and Jacob Goldberger
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:416318
  10. A fundamental problem in signal processing is to estimate signal from noisy observations. This is usually formulated as an optimization problem. Optimizations based on variational lower bound and minorization-...

    Authors: Guang Deng and Wai-Yin Ng
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:429128
  11. This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP), which is based on Daugman's method for iris recognition and the local XOR pattern (...

    Authors: Baochang Zhang, Zongli Wang and Bineng Zhong
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:469109
  12. We present an algorithm for the on-board vision vehicle detection problem using a cascade of boosted classifiers. Three families of features are compared: the rectangular filters (Haar-like features), the hist...

    Authors: Pablo Negri, Xavier Clady, Shehzad Muhammad Hanif and Lionel Prevost
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:782432
  13. Marker-driven watershed segmentation attempts to extract seeds that indicate the presence of objects within an image. These markers are subsequently used to enforce regional minima within a topological surface...

    Authors: Ilya Levner, Hong Zhang and Russell Greiner
    Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:485821