text: Gabor filters (GFs) play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved GFs that locally adapt their shape to the direction of flow. These curved GFs enable the choice of filter parameters that increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved GFs are applied to the curved ridge and valley structures of low-quality fingerprint images. First, we combine two orientation-field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation. Subsequently, these curved regions are used for estimating the local ridge frequency. Finally, curved GFs are defined based on curved regions, and they apply the previously estimated orientations and ridge frequencies for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison with state-of-the-art enhancement methods.
  @cite_30: Two-dimensional spatial linear filters are constrained by general uncertainty relations that limit their attainable information resolution for orientation, spatial frequency, and two-dimensional (2D) spatial position. The theoretical lower limit for the joint entropy, or uncertainty, of these variables is achieved by an optimal 2D filter family whose spatial weighting functions are generated by exponentiated bivariate second-order polynomials with complex coefficients, the elliptic generalization of the one-dimensional elementary functions proposed in Gabor’s famous theory of communication [ J. Inst. Electr. Eng.93, 429 ( 1946)]. The set includes filters with various orientation bandwidths, spatial-frequency bandwidths, and spatial dimensions, favoring the extraction of various kinds of information from an image. Each such filter occupies an irreducible quantal volume (corresponding to an independent datum) in a four-dimensional information hyperspace whose axes are interpretable as 2D visual space, orientation, and spatial frequency, and thus such a filter set could subserve an optimally efficient sampling of these variables. Evidence is presented that the 2D receptive-field profiles of simple cells in mammalian visual cortex are well described by members of this optimal 2D filter family, and thus such visual neurons could be said to optimize the general uncertainty relations for joint 2D-spatial–2D-spectral information resolution. The variety of their receptive-field dimensions and orientation and spatial-frequency bandwidths, and the correlations among these, reveal several underlying constraints, particularly in width length aspect ratio and principal axis organization, suggesting a polar division of labor in occupying the quantal volumes of information hyperspace. Such an ensemble of 2D neural receptive fields in visual cortex could locally embed coarse polar mappings of the orientation–frequency plane piecewise within the global retinotopic mapping of visual space, thus efficiently representing 2D spatial visual information by localized 2D spectral signatures.
  @cite_1: This paper proposes an automated blood vessel detection scheme based on adaptive contrast enhancement, feature extraction, and tracing. Feature extraction of small blood vessels is performed by using the standard deviation of Gabor filter responses. Tracing of vessels is done via forward detection, bifurcation identification, and backward verification. Tests over twenty images show that for normal images, the true positive rate (TPR) ranges from 80 to 91 , and their corresponding false positive rates (FPR) range from 2.8 to 5.5 . For abnormal images, the TPR ranges from 73.8 to 86.5 and the FPR ranges from 2.1 to 5.3 , respectively. In comparison with two published solution schemes that were also based on the STARE database, our scheme has lower FPR for the reported TPR measure.
  @cite_52: tion. Generally, finger-vein images have low contrast and uneven illumination due to finger-vein imaging manner and finger-shape variation. So, finger-vein enhancement is indispensable for reliable finger-vein network extraction. This paper proposes a new method based on combination of Gray-Level Grouping (GLG) and Circular Gabor Filter (CGF) for finger-vein image enhancement. First, GLG is used to reduce illumination fluctuation and improve the contrast of finger-vein images. Then a circular Gabor filter is used to further strengthen vein ridges in images. The experimental results show that this proposed method is capable of enhancing finger-vein image effectively.
  @cite_59: Multi-channel filtering implemented using the Gabor function, or Gabor filter, is capable of mimicking characteristics of the human visual system. In the assessment of osteoporosis, Gabor filter is used to calculate features from a trabecular pattern recorded on radiographs of a proximal femur. The assessment of osteoporosis can be done by observing and analyzing the trabecular pattern in the proximal femur. The feature extraction method used is energy calculation. The energy then is used for assessment or classification. The predetermined Singh index of the trabecular pattern is used to justify the classification result.
  @cite_31: Abstract Frequency-specific, i.e., narrow-band brain, activity is traditionally analyzed on the basis of either a time- or frequency-domain representation of the signal. Here we demonstrate an alternative method based on Gabor functions which are well known for their optimal concentration in time and frequency. Using Gabor filtering, amplitude and frequency information can be separated clearly from one another and certain novel approaches to averaging become possible.
  @cite_34: In this study, the Gabor filter bank technique was applied to the biceps and gastrocnemius ultrasound images to longitudinally enhance the coherently oriented and hyperechoic perimysiums regions. The method involved three steps, orientation field estimation, frequency map computation and Gabor filtering. The method was evaluated using a simulated image distorted with multiplicative speckle noises, where the “muscles” were arranged in a bipennate fashion with a central “aponeurosis”. After the enhancement using the proposed method, most of the original hyperechoic bands in the simulated image could be recovered and the noises in other locations were greatly reduced. The proposed method was also tested on biceps sonograms collected from 4 healthy adult subjects. Based on the filtering results, the hyperechoic regions, especially the fibroadipose septas, could be enhanced in several aspects, such as the completion of broken but coherently oriented regions. It is believed that the proposed method have potentials in assisting the visualization of strongly oriented patterns in ultrasound images and especially the quantitative estimation of muscle thickness, muscle fiber pennation angle and fascicle length.
summary: In medical imaging, GFs are applied for the enhancement of structures like e.g. finger veins @cite_52 and muscle fibers in ultrasound images @cite_34 , for the detection of blood vessels in retinal images @cite_1 , as well as for many other tasks like e.g. analyzing event-related brain activity @cite_31 , assessing osteoporosis in radiographs @cite_59 and for modeling the behavior of simple cells in the mammalian visual cortex @cite_30 .