The architecture and implementation of a rule-based fuzzy approach to the detection and classification of man made objects in satellite image data are presented. In a first processing step fuzzy clustering is used to obtain an initial coarse presegmentation of the data. Subsequently, a rule-based fuzzy system performs the classification. Its rules are generated both manually (based on common-se...

1. Preface Recently, the research on the ontology has been spread widely to be critical components in the knowledge management, Semantic Web, business-to-business applications, and several other application areas. In this article, I would like to introduce some applications of domain ontology presented by my research team in Taiwan, including“an ontology-based fuzzy image filter and its applica...

Images are imitations of factual world substances. Processing it to get better visualization is called as image processing. With the increasing availability and decreasing cost of satellite imagery, the Remote sensing image enhancement, segmentation and classification has become the most important research issue in field of Remote sensing. In this proposed work, Land sat 7 Remote Sensing images...

Matching of binary image features is an important step in many different computer vision applications. Conventionally, an arbitrary threshold is used to identify a correct match from incorrect matches using Hamming distance which may improve or degrade the matching results for different input images. This is mainly due to the image content which is affected by the scene, lighting and imaging co...

Image denoising is one of the important image processing techniques to reduce noises from a corrupted image. This paper proposes a new efficient fuzzy based filter for the restoration of images that are corrupted with Gaussian noise in gray and color images. This filter is applied iteratively to reduce heavy noise in images. The proposed scheme is simulated using standard image of lena under di...

Due to the increase in need of transmission of images in computer, mobile environments, the research in the field of image compression has increased significantly. Image compression plays a important role in digital image processing. In this paper image compression is done using slant transform exploiting the characteristics of Human Visual System (HVS). Normally JPEG compressors support variab...

Digital imaging devices become popular and have replaced analog ones since the invention and development of digital signal processing technology several years ago. A common problem in digital image is noise, which is often happened when the imaging devices such as digital camera, cctv, camcorder, are used in a poor lighting scene. To overcome this problem, many methods have been introduced. We ...

Medical image segmentation plays a vital role in image processing due to the catering needs of the medical images in automating, delineating anatomical structures and diagnosis. Very often the medical images contain uncertain, vague, and incomplete data definition. The concepts of lower and upper approximations of rough sets effectively handle this data. In this paper, rough sets based clusteri...

Processing biological data often requires handling of uncertain and sometimes inconsistent information. Particularly when coping with image segmentation tasks against biomedical background, a clear description of for example tissue borders is often hard to obtain. On the other hand, there are only a few promising segmentation algorithms being able to process fuzzy input data. This paper describ...

Removing mixed noise from digital images is a challenging problem as it involves processing of various types of noise. Additionally, noises should be differentiated from inherent image structures. Fuzzy logic is a successful solution in this situation. In this paper, we propose a novel fuzzy technique to reduce mixed ImpulseGaussian noise from color images. A weighted averaging process is used ...