According to the problem of low positioning accuracy of the existing line detection algorithm and multiple response problem of the single edge detection, this paper presents an improved Hough transform based on Canny operator object detection algorithm which uses the characters of the line segment object from the commonly used edge detection operator to find the best comprehensive properties of...

Edge detection from images is one of the most important concerns in digital image and video processing. Edge detection is very useful in computer vision for extracting meaningful information from images. Real time edge detection is implemented on the platform that consists of the TMS320DM6437 DSP, camera, TV tuner, Display and canny edge detection algorithm. The main goal of our technique is to...

The novelty of this paper is edge detection in binary and color images using the Ricci curvature function is proposed. The reason for this is, if the edges in an image are determined accurately, then all of the objects can be located and basic image properties can be measured. In this paper we represent images as a manifold and make use of differential geometry in image processing, namely the R...

Performing image acquisition and processing can require a high amount of computational resource. In this article, I am discussing the application Canny Edge Detection algorithm to live webcam real-time using NI’s software environment.

This paper presents a hybrid edge detection algorithm in situations where the image is corrupted by Saltand-Pepper noise. Edge detection is an important preprocessing step in image analysis. Successful results of image analysis extremely depend on edge detection. Up to now several edge detection methods have been developed such as Roberts, Prewitt, Sobel, Zero-crossing, Canny, etc. But, they ar...

The objective of this paper is to present the hybrid approach for edge detection. Under this technique, edge detection is performed in two phase. In first phase, Canny Algorithm is applied for image smoothing and in second phase neural network is to detecting actual edges. Neural network is a wonderful tool for edge detection. As it is a non-linear network with built-in thresholding capability....

We propose a biologically motivated computational step, called surround inhibition, which improves the performance of contour detectors. The mechanism of surround inhibition is exhibited by the majority of the orientation selective neurons in the primary visual cortex of macaque monkeys and has been demonstrated to influence the visual perception of man as well. We illustrate the principle and ...

Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. This paper introduces a new classification of most important and commonly used edge detection algorithms, namely ISEF, Canny, Marr-Hildreth, Sobel, Kirsch, Lapla1 and Lapla2. Five categories are included in our classification, and then advan...

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapp...