Both types of representations are useful when one wishes to consider image data as a continuum rather than a discrete array of pixels. Such a continuous modeling of the data is often required in medical imaging. Interpolation, in particular, plays a crucial role at various stages of processing [18, 24]. For instance, it is present—explicitly or not—for tomographic reconstruction, irrespective o...

Optical character recognition (OCR) is one of the most successful application of pattern recognition and image processing. Character geometry is one of the most useful feature for identifying characters in images. The geometric feature extraction techniques proposed in literature are complex and requires extensive effort in implementation. In this paper, we propose a preprocessing technique whi...

-------------------------------------------------------------------ABSTRACT--------------------------------------------------------------Fingerprint recognition is a promising factor for the Biometric Identification and authentication process. The quality of the fingerprint is obtained by the noise free image. To get a noise-free fingerprint image, the preprocessing techniques are applied on im...

Tensor-driven anisotropic diffusion and regularisation have been successfully applied to a wide range of image processing and computer vision tasks such as denoising, inpainting, and optical flow. Empirically it has been shown that anisotropic models with a diffusion tensor perform better than their isotropic counterparts with a scalar-valued diffusivity function. However, the reason for this s...

Assessment for image quality traditionally needs its original image as a reference. The conventional method for assessment like Mean Square Error (MSE) or Peak Signal to Noise Ratio (PSNR) is invalid when there is no reference. In this paper, we present a new No-Reference (NR) assessment of image quality using blur and noise. The recent camera applications provide high quality images by help of...

Spectral clustering methods have been shown to be effective for image segmentation. Unfortunately, the presence of image noise as well as textural characteristics can have a significant negative effect on the segmentation performance. To accommodate for image noise and textural characteristics, this study introduces the concept of sub-graph affinity, where each node in the primary graph is mode...

The segmentation of tree-like tubular structures such as coronary arteries and airways is an essential step for many 3D medical imaging applications. Statistical tracking techniques for the extraction of elongated structures have received considerable attention in recent years due to their robustness against image noise and pathological changes. However, most tracking methods are limited to a s...

OBJECTIVE The purpose of this study was to evaluate the image noise, low-contrast resolution, image quality, and spatial resolution of adaptive statistical iterative reconstruction in low-dose body CT. MATERIALS AND METHODS Adaptive statistical iterative reconstruction was used to scan the American College of Radiology phantom at the American College of Radiology reference value and at one-ha...