automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. most of the road detection approaches are based on image segmentation algorithms. color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. in order to reduce the light change ...

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

Edge detection and edge enhancement techniques play an essential role in interpreting potential field data. This paper describes the application of various edge detection techniques to gravity data in order to delineate the edges of subsurface structures. The edge detection methods comprise analytic signal, total horizontal derivative (THDR), theta angle, tilt angle, hyperbolic of tilt angle (H...

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

one of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of an image where the preciseness and reliability of its results will affect directly on the comprehension machine system made objective world. several edge detectors have been developed in the past decades, although no single edge detector...

in this paper, by means of fuzzy approaches, an accurate method is introduced for edging of color photographs. the difference between our method with other similar methods is the use of a morphological operation to think or thick the obtained edges. in this proposed method, a 3×3 window is dragged on the photo. for each block, 12 point sets will be defined, each including two non-overlapping po...

in this paper, we present an edge detection method based on wavelet transform and hessian matrix of image at each pixel. many methods which based on wavelet transform, use wavelet transform to approximate the gradient of image and detect edges by searching the modulus maximum of gradient vectors. in our scheme, we use wavelet transform to approximate hessian matrix of image at each pixel, too. ...

edge detection and edge enhancement techniques play an essential role in interpreting potential field data. this paper describes the application of various edge detection techniques to gravity data in order to delineate the edges of subsurface structures. the edge detection methods comprise analytic signal, total horizontal derivative (thdr), theta angle, tilt angle, hyperbolic of tilt angle (h...

One of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of an image where the preciseness and reliability of its results will affect directly on the comprehension machine system made objective world. Several edge detectors have been developed in the past decades, although no single edge detector...