An Analysis of Normalized Correlation Image Matching by Genetic Algorithm
نویسندگان
چکیده
منابع مشابه
Deep Learning Improves Template Matching by Normalized Cross Correlation
Template matching by normalized cross correlation (NCC) is widely used for finding image correspondences. We improve the robustness of this algorithm by preprocessing images with "siamese" convolutional networks trained to maximize the contrast between NCC values of true and false matches. The improvement is quantified using patches of brain images from serial section electron microscopy. Relat...
متن کاملTemplate Matching using Fast Normalized Cross Correlation
In this paper we present an algorithm for fast calculation of the normalized cross correlation NCC and its applica tion to the problem of template matching Given a template t whose position is to be determined in an image f the basic idea of the algorithm is to represent the template for which the normalized cross correlation is calculated as a sum of rectangular basis functions Then the correl...
متن کاملEquipment capacity optimization of an educational building’s CCHP system by genetic algorithm and sensitivity analysis
Combined cooling, heating, and power (CCHP) systems produce electricity, cooling, and heat due to their high efficiency and low emission. These systems have been widely applied in various building types, such as offices, hotels, hospitals and malls. In this paper, an economic and technical analysis to determine the size and operation of the required gas engine for specific electricity, cooling, ...
متن کاملImage Matching by Multiscale Oriented Corner Correlation
In this paper we present a simple but effective method for matching two uncalibrated images. Feature points are firstly extracted in each image using a fast multiscale corner detector. Each feature point is assigned with one dominant orientation. The correspondence of feature points is then established by utilizing a multilevel matching strategy. We employ the normalized cross-correlation defin...
متن کاملHybrid image matching combining Hausdorff distance with normalized gradient matching
Image matching has been a central problem in computer vision and image processing for decades. Most of the previous approaches to image matching can be categorized into the intensity-based and edge-based comparison. Hausdorff distance has been widely used for comparing point sets or edge maps since it does not require point correspondences. In this paper, we propose a new image similarity measu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEJ Transactions on Electronics, Information and Systems
سال: 2000
ISSN: 0385-4221,1348-8155
DOI: 10.1541/ieejeiss1987.120.2_236