Image segmentation is very essential and critical to image processing and pattern recognition. In this paper, a technique for color image segmentation called ‘Adaptive Neuro-Fuzzy Color Image Segmentation (ANFIS)’ is proposed. Adaptive Neuro-Fuzzy system is used for automatic multilevel image segmentation. This system consists of multilayer perceptron (MLP) like network that performs color imag...

One of the key issues in microarray analysis is to extract quantitative information from the spots, which represents gene expression levels in the experiments. The process of identifying the spots and separating the foreground from the background is known as microarray image segmentation. In this paper, we propose a new approach to microarray image segmentation, which we called the adaptive ell...

Fingerprint image segmentation is part of pre-processing in fingerprint image recognition system. It has a critical effect to the fingerprint image recognition system. Regardless of years of research in the area of general purpose image segmentation, it is still a very challenging task. A new image decomposition scheme, called the Adaptive and Orientation algorithm, is proposed to achieve effec...

Elastic image registration is widely used to adapt brain images to a common template space, and, in complementary fashion, to adapt an anatomical template to a subject's anatomy. Although HAMMER is a very accurate image-registration algorithm, it requires a 3-class segmentation step prior to registration, and its performance is affected by segmentation quality. We here propose a new framework t...

An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous regi...

Previous works on range image segmentation concentrate on surface patches that can be well represented by certain mathematical functions. In this paper we consider the more qualitative segmentation problem of decomposing a range image into convex parts/objects. An edge-based approach is proposed which uses an adaptive contour closure algorithm in conjunction with a global convexity test. Experi...

This thesis presents the development of a theoretical framework capable of encompassing the colour and texture information in a robust image descriptor that can be applied to the identification of coherent regions in complex natural images. In the suggested approach, the colour and texture features are extracted explicitly on two independent channels and the main emphasis of this work was place...

In recent times, capturization of video became more feasible with the advanced technologies in camera. Those videos get easily contaminated by noise due to the characteristics of image sensors. Surveillance sequences not only have static scenes but also dynamic scenes. Many efforts have been taken to reduce video noise. Averaging the frame as an image had limited denoising effect and resulted i...

reducing the number of colors in an image while preserving its quality, is of importance in many applications such as image analysis and compression. it also decreases memory and transmission bandwidth requirements. moreover, classification of image colors is applicable in image segmentation and object detection and separation, as well as producing pseudo-color images. in this paper, the kohene...

introduction breast cancer is one of the most common types of cancer among women.  early detection of breast cancer is the key to reducing the associated mortality rate. the presence of microcalcifications clusters (mccs) is one of the earliest signs of breast cancer. due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...