Algorithms for automatic image registration and mosaicking are developed for a miniature Unmanned Aerial Vehicle (MINI-UAV) platform, assembled by Air-O-Space International (AOSI) L.L.C.. Three cameras onboard this MINI-UAV platform acquire images in a single frame simultaneously at green (550nm), red (650 nm), and near infrared (820nm) wavelengths, but with shifting and rotational misalignment. The area-based method is employed in the developed algorithms for control point detection, which is applicable when no prominent feature details are present in image scenes. Because the three images to be registered have different spectral characteristics, region of interest determination and control point selection are the two key steps that ensure the quality of control points. Affine transformation is adopted for spatial transformation, followed by bilinear interpolation for image resampling. Mosaicking is conducted between adjacent frames after three-band co-registration. Pre-introducing the rotation makes the area-based method feasible when the rotational misalignment cannot be ignored. The algorithms are tested on three image sets collected at Stennis Space Center, Greenwood, and Oswalt in Mississippi. Manual evaluation confirms the effectiveness of the developed algorithms. The codes are converted into a software package, which is executable under the Microsoft Windows environment of personal computer platforms without the requirement of MATLAB or other special software support for commercial-off-the-shelf (COTS) product. The near real-time decision-making support is achievable with final data after its installation into the ground control station. The final products are color-infrared (CIR) composite and normalized difference vegetation index (NDVI) images, which are used in agriculture, forestry, and environmental monitoring.

No description available.

The aim of this thesis was to make a program for object finding, object segmentation and similarity object detection in the image. Object are representing by cars. Description of image making, image preprocessing, geometrical transform and Hough transform was written in the theoretical part of the thesis. Also basic morphological operations, corner detection algorithms and methods of object similarity detection were described in this part. The practical part of the thesis focus to realization of single segments from how to make image, through main program analysis and auxiliary functions to similarity results evaluation. Main program is devided to four parts. The program is preprocessed in the first part. The geometrical transforms are used in the second part and the object similarity is detected in the third part. The last part shows the results. The algorithm is realized in C++ language using the OpenCV library.