Detection of Edges Using Two-Way Nested Design
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 3
Abstract
This paper implements a novel approach of identifying edges in images using a two-way nested design. The test comprises of two steps. First step is based on an F-test. The sums of square (SS) of various effects are used to extract the mean square (MS) effect of respective effects and the unknown effect considered as noise. The mean square value has a chi-square distribution. The ratio of two chi-square distributions has an F-distribution. The final decision is based on testing a hypothesis for the presence or absence of an effect. The second step is based on contrast function (CF). This test identifies the presence or absence of an edge in four directions that are horizontal, vertical, and the two diagonal directions. The test is based on Tukey’s T-test. The performance of nested design is compared with the edge detection using Sobel filter. A rigorous testing reveals that the nested design yields comparable results for images that are either free of noise or corrupted with light noise. The nested design however outperforms the Sobel filter in situations where the images are corrupted with heavy noise.
Authors and Affiliations
Asim ur Rehman Khan, Syed Muhammad Atif Saleem, Haider Mehdi
Keywords
Related Articles
- EP ID EP249619
- DOI 10.14569/IJACSA.2017.080321
- Views 103
- Downloads 0
Using the Technology Acceptance Model in Understanding Academics’ Behavioural Intention to Use Learning Management Systems
Although e-learning is in its infancy in Saudi Arabia, most of the public universities in the country show a great interest in the adoption of learning and teaching tools. Determining the significance of a particular too...
On the Projection Matrices Influence in the Classification of Compressed Sensed ECG Signals
In this paper the classification results of compressed sensed ECG signals based on various types of projection matrices is investigated. The compressed signals are classified using the KNN (K-Nearest Neighbour) algorithm...
Feature Weight Optimization Mechanism for Email Spam Detection based on Two-step Clustering Algorithm and Logistic Regression Method
This research proposed an improved filtering spam technique for suspected emails, messages based on feature weight and the combination of two-step clustering and logistic regression algorithm. Unique, important features...
A Congestion Avoidance Approach in Jumbo Frame-enabled IP Network
Jumbo frame is as an approach that allows for higher utilization of larger packet sizes on a domain-wise basis, decreasing the number of packets processed by core routers while not having any adverse impact on the...
Educational Data Mining Model Using Rattle
Data Mining is the extraction of knowledge from the large databases. Data Mining had affected all the fields from combating terror attacks to the human genome databases. For different data analysis, R programming has a k...