IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for subpixel registration
Computer Vision, Graphics, and Image Processing
A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust regression and outlier detection
Robust regression and outlier detection
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of automated visual inspection
Computer Vision and Image Understanding
Efficiently Locating Objects Using the Hausdorff Distance
International Journal of Computer Vision
Recovering Affine Motion and Defocus Blur Simultaneously
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Scale Control for Edge Detection and Blur Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting the Optimal Focus Measure for Autofocusing and Depth-From-Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Computer Vision by Cooperative Focus and Stereo
Active Computer Vision by Cooperative Focus and Stereo
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of focus measures in multi-focus image fusion
Pattern Recognition Letters
A Two-Stage Cross Correlation Approach to Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Noise insensitive focus value operator for digital imaging systems
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Object matching algorithms using robust Hausdorff distance measures
IEEE Transactions on Image Processing
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Pattern localization is a fundamental task in machine vision, and autofocus is a requirement for any automated inspection system by allowing greater variation in the distance from the camera to the object being imaged. In this paper, we propose a unified approach to simultaneous autofocus and alignment for pattern localization by extending the idea of image reference approach. Under the least trimmed squares (LTS) scheme, the proposed hybrid weighted Hausdorff distance (HWHD) is a robust similarity metric that combines the Hausdorff distance (HD) with the edge-amplitude normalized gradient (EANG) matching. The EANG is designed to characterize the different degrees of blur at the edge points for focus cues, immune to illumination variations between the reference and the target image. We experimentally illustrate its performance on simulated as well as real data.