A new edge detection approach based on image context analysis

Yu, Yuanhui; Chang, Chin‐Chen

doi:10.1016/j.imavis.2006.03.006

Cited by 45 publications

(26 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The sobel operator is used mostly for detecting vertical and horizontal edges [3][5]. The edges detected by this sobel operator may not be suitable for all the applications [7]. As per the Sobel Edge Detection the images of the three species of Prawn are shown in Figure2.…”

Section: Figure2: Sobel Filtermentioning

confidence: 99%

“…The first step in this detector is to filter out noise in the image by using a Gaussian smoothing filter [10]. g(m,n)=G (m,n)*f(m,n) the edge in the edge direction and set the pixel that is not at the maximum to be 0, which is called non-maximum suppression [7]. Finally the edges are detected and linked using pixel connectivity and double thresholding that is, if the magnitude is above the high threshold, then it is considered as an edge.…”

Section: Canny's Edge Detectormentioning

confidence: 99%

See 1 more Smart Citation

A Comparative Study on Various Edge Detection Techniques used for the Identification of Penaeid Prawn Species

Sucharita¹,

Jyothi²,

Mamatha³

2013

IJCA

View full text Add to dashboard Cite

Section: Figure2: Sobel Filtermentioning

confidence: 99%

Section: Canny's Edge Detectormentioning

confidence: 99%

A Comparative Study on Various Edge Detection Techniques used for the Identification of Penaeid Prawn Species

Sucharita¹,

Jyothi²,

Mamatha³

2013

IJCA

View full text Add to dashboard Cite

“…Sobel), Gaussian based (e.g. LoG), multi-resolution [17], non-linear [18], wavelet based [19], statistical [20], machine learning based [21], contextual [22] and line edge [23] methods.…”

Section: Edge Detectionmentioning

confidence: 99%

Illumination Invariant Facial Pose Classification

Jaiswal¹,

Kumar²,

Agrawal³

2012

IJCA

View full text Add to dashboard Cite

In this paper, we compared the performance of various combinations of edge operators and linear subspace methods to determine the best combination for pose classification. To evaluate the performance, we have carried out experiments on CMU-PIE database which contains images with wide variation in illumination and pose. We found that the performance of pose classification depends on the choice of edge operator and linear subspace method. The best classification accuracy is obtained with Prewitt edge operator and Eigenfeature regularization method. In order to handle illumination variation, we used adaptive histogram equalization as a preprocessing step resulting into significant improvement in performance except for Roberts operator.

show abstract

“…Edge detection has received much attention during the past two decade because of its significant importance in many research areas [1]. Since, the edge is a prominent feature of an image; it is the front-end processing stage in object recognition and image understanding system.…”

Section: Introductionmentioning

confidence: 99%

Novel Approach of Edges Detection for Digital Images Based On Hybrid Types of Entropy

El-Sayed¹,

Bahgat²,

Abdel‐Khalek³

2013

Appl. Math. Inf. Sci.

View full text Add to dashboard Cite

Edges detection of digital images is used in a various fields of applications ranging from real-time video surveillance and traffic management to medical imaging applications. Most of the classical methods for edge detection are based on the first and second order derivatives of gray levels of the pixels of the original image. These processes give rise to the exponential increment of computational time. This paper shows the new algorithm based on both the Tsallis entropy and the Shannon entropy together for edge detection using split and merge technique. The objective is to find the best edge representation and minimize the computation time. A set of experiments in the domain of edge detection are presented. An edge detection performance compared to the previous classic methods, such as Canny, LOG, and Sobel. Analysis show that the effect of the proposed method is better than those methods in execution time and also is considered as easy implementation

show abstract

A new edge detection approach based on image context analysis

Cited by 45 publications

References 16 publications

A Comparative Study on Various Edge Detection Techniques used for the Identification of Penaeid Prawn Species

A Comparative Study on Various Edge Detection Techniques used for the Identification of Penaeid Prawn Species

Illumination Invariant Facial Pose Classification

Novel Approach of Edges Detection for Digital Images Based On Hybrid Types of Entropy

Contact Info

Product

Resources

About