A real-time high performance edge detector for computer vision applications

Alzahrani, Fahad M; Chen, T.

doi:10.1109/aspdac.1997.600357

Cited by 5 publications

(7 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed technique has used edge detection and contour detection techniques for noise estimation. Section 3.1 presents Absolute Difference Mask (ADM) [2] for edge maps construction and Section 3.2 presents proposed quality estimation process.…”

Section: Proposed Techniquementioning

confidence: 99%

“…We have utilized Absolute Difference Mask (ADM) [2] in order to find out the edge strength, edge direction and finally edge map. In ADM, first of all the absolute difference of pixels is computed and then with these differences, strength and direction are find out.…”

Section: Edge Maps Constructionmentioning

confidence: 99%

“…In this paper, we introduce a new way for no reference image quality assessments based on noise detection. The Proposed technique has utilized Absolute Difference Mask (ADM) [2] for edge detection and compute contours in image in order to numerate all edges and assess the quality.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Image quality assessment based on noise detection

Joshi

Prakash

2014

2014 International Conference on Signal Processing and Integrated Networks (SPIN)

View full text Add to dashboard Cite

A new technique for image quality assessment based on noise detection is devised in this paper. Many applications like face recognition, ear recognition etc. are dependent on training images. Poor quality training images lead to inefficient training which in turn degrades the performance of a biometric system. This paper has proposed a technique for quality estimation of biometric images. The technique does not need any reference image for image quality assessment. Experimental analysis has shown the efficiency of the proposed technique.

show abstract

Section: Proposed Techniquementioning

confidence: 99%

Section: Edge Maps Constructionmentioning

confidence: 99%

See 1 more Smart Citation

Image quality assessment based on noise detection

Joshi

Prakash

2014

2014 International Conference on Signal Processing and Integrated Networks (SPIN)

View full text Add to dashboard Cite

show abstract

“…This technique is based on principle that the difference between the noisy pixel and the nearest good pixel will be different from the difference between two nearby good pixels. A noise based quality estimation technique proposed in [3] has utilized Absolute Difference Mask (ADM) [1] and detect contours for counting all edges. This technique has constructed edge maps using ADM and in each edge map number of edges are counted.…”

Section: Literature Surveymentioning

confidence: 99%

“…It has utilized our previously proposed technique [3] for estimation of image quality based on noise. This technique has used Absolute difference mask (ADM) [1] for edge detection and computes contours to numerate all edges in image. Image quality is estimated using obtained contours information.…”

Section: Introductionmentioning

confidence: 99%

A quality aware technique for biometric recognition

Joshi

Prakash

2015

2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN)

View full text Add to dashboard Cite

Noise is a very common factor for degradation of images and for better performance of any image based biometric system, enhancement of poor quality images due to noise is necessary. In most of the previously proposed techniques in the literature, it is assumed that all the images participating in the recognition process are of poor quality and an enhancement technique is blindly applied to all the images to enhance them. For example, apply Gaussian smoothing on all the images to make them noise free, however, such blind application of image enhancement degrades the quality of good images. This paper presents a quality aware technique for biometric recognition. It has utilized our previously proposed technique for image quality assessment based on noise detection. The technique first estimates the quality of the images used in the recognition and if the quality value is found to be below a certain threshold, an enhancement is applied on the image before using it for recognition. Experimental analysis has been conducted on Yale Extended Cropped Face Database. Obtained results show the effectiveness of the proposed technique.

show abstract