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Comparison of Edge Localization Performance of Moment-Based Operators Using Target Image Data
( Suyoung Seo ) 대한원격탐사학회 2016 大韓遠隔探査學會誌 Vol.32 No.1
This paper presents a method to evaluate the performance of subpixel localization operators using target image data. Subpixel localization of edges is important to extract the precise shape of objects from images. In this study, each target image was designed to provide reference lines and edges to which the localization operators can be applied. We selected two types of moment-based operators: Gray-level Moment (GM) operator and Spatial Moment (SM) operator for comparison. The original edge localization operators with kernel size 5 are tested and their extended versions with kernel size 7 are also tested. Target images were collected with varying Camera-to-Object Distance (COD). From the target images, reference lines are estimated and edge profiles along the estimated reference lines are accumulated. Then, evaluation of the performance of edge localization operators was performed by comparing the locations calculated by each operator and by superimposing them on edge profiles. Also, enhancement of edge localization by increasing the kernel size was also quantified. The experimental result shows that the SM operator whose kernel size is 7 provides higher accuracy than other operators implemented in this study.
( Suyoung Seo ) 대한원격탐사학회 2016 大韓遠隔探査學會誌 Vol.32 No.1
This paper presents a set of methods to evaluate the image quality of smartphone cameras as compared with that of a DSLR camera. In recent years, smartphone cameras have been used broadly for many purposes. As the performance of smartphone cameras has been enhanced considerably, they can be considered to be used for precise mapping instead of metric cameras. To evaluate the possibility, we tested the quality of one DSLR camera and 3 smartphone cameras. In the first step, we compare the amount of lens distortions inherent in each camera using camera calibration sheet images. Then, we acquired target sheet images, extracted reference lines from them and evaluated the geometric quality of smartphone cameras based on the amount of errors occurring in fitting a straight line to observed points. In addition, we present a method to evaluate the radiometric quality of the images taken by each camera based on planar fitting errors. Also, we propose a method to quantify the geometric quality of the selected camera using edge displacements observed in target sheet images. The experimental results show that the geometric and radiometric qualities of smartphone cameras are comparable to those of a DSLR camera except lens distortion parameters.
Estimation of edge displacement against brightness and camera-to-object distance
IET 2017 IET image processing Vol.11 No.8
<P>This study proposes a systematic method to estimate edge displacement (ED) from ground truth edges. To obtain ground truth edges and test edges, a series of target sheets containing the reference regions and brightness contrast regions were designed. Further, the brightness contrast regions were designed to contain foreground and background brightness between which the image edges occur. By varying the foreground brightness (FB), the influence of the FB on the edge locations was tested. Moreover, the influence of camera-to-object distance on the edge locations was tested. A simple least-squares method using slope profiles and a slope-based weighting scheme is proposed for calculating the edges occurring in contrast regions with subpixel accuracy. The experiment results revealed that a bright foreground moves the edge location towards the dark side of the edges in the range of 0-0.6 pixels with strong relationships between the FB and magnitude of ED.</P>
Subpixel Edge Localization Based on Adaptive Weighting of Gradients
IEEE 2018 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.27 No.11
<P>This paper presents a subpixel edge localization method based on the adaptive weighting of gradients (AWG). The method first finds the optimal power factors to be used by the AWG through an error propagation scheme. Then, with the goal of fast implementation of the method, a process that directly relates the edge width to the optimal powers is proposed. A method that uses the squared weighting of gradients (SWG) is also proposed, which applies a power of 2 to the gradients of an edge profile to calculate the edge location with subpixel accuracy. Next, an enhanced version of the AWG that combines the SWG and AWG selectively is proposed to obtain the best localization. At present, a fitting method based on the error function (Erf) is considered to be the most accurate method among current state-of-the-art methods, but it has a very high computational cost. The experimental results show that the proposed method is computationally much less expensive and more accurate than the Erf-fitting method.</P>
Edge Modeling by Two Blur Parameters in Varying Contrasts
IEEE 2018 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.27 No.6
<P>This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.</P>