This paper describes a new method of extraction and clustering of edges in images. The proposed method results a graph of detected edges instead of a binary mask of the edge pixels. The developed algorithm contains a sequential pixel-level scan, and a much smaller second and third pass on the results to determine the connectivities. It is therefore significantly faster than Canny edge detector,...

Edge detection is used widely from consumer applications to military and medical image analysis. One of the challenges in edge detection is getting the best trade-off between reliable detection and noise robustness. Because of that it is important to develop reliable edge detection algorithm which can adapt to different noise levels keeping false detections at minimum. In this paper we propose ...

In this paper, we propose a Cellular Edge Detection (CED) algorithm which utilizes Cellular Automata (CA) and Cellular Learning Automata (CLA). The CED algorithm is an adaptive, intelligent and learnable algorithm for edge detection of binary and grayscale images. Here, we introduce a new CA local rule with adaptive neighborhood type to produce the edge map of image as opposed to CA with fixed ...

Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. To extract important information from an MRI medical images, an efficient image segmentation or edge detection is required. Edges are represented as important contour features in the medical image since they are the boundaries where...

Edges are a robust feature for object detection. In this paper, we present an edge-based background modeling method for the detection of moving objects. The edges in the image frames were mapped using robust Canny edge detector. Two edge maps were created and combined to calculate the ultimate moving-edge map. By selecting all the edge pixels of the current frame above the defined threshold of ...

This proposed work discusses about the breast cancer detection at the earlier stage on mammogram images using k-means algorithm. This approach has been done in three steps. The primary step is pre-processing, which removes noises in the images. Then canny edge detection is used to detect the edges of images. After finding the edges morphological operation is done to get clear mass. Then origina...

In this paper we propose a method to detect human faces in color images , that uses a combination of color spaces and edge detection for segmentation. Algorithm ingeniously combines different color space models, specifically, HSI and YCbCr along with Canny and Prewitt edge detection techniques.Experimental results indicate improved false acceptance rates. The overall performance of the face det...

This paper proposes an algorithm for detecting artificial text in video frames using edge information. First, an edge map is created using the Canny edge detector. Then, morphological dilation and opening are used in order to connect the vertical edges and eliminate false alarms. Bounding boxes are determined for every non-zero valued connected component, consisting the initial candidate text a...

OBJECTIVES The purpose of this study was to investigate the ability of quantitative ultrasound (US) using edge detection analysis to assess patients with Duchenne muscular dystrophy (DMD). METHODS After Institutional Review Board approval, US examinations with fixed technical parameters were performed unilaterally in 6 muscles (biceps, deltoid, wrist flexors, quadriceps, medial gastrocnemius,...