Image Mosaic Using FAST Corner Detection

The main concept behind the image mosaic is image registration. The image mosaic can be defined as the automatic alignment or registration of multiple images into larger aggregates with two simultaneous images having some similarities between them. Image registration is an important part of the image processing and computer vision. On the basis of analyzing two types of image registration, an automated image registration method was put forward to dealing with image registration with similar transformation. SUSAN and Harris corner detection algorithms which are both based on intensity, were compared in stability, noise immunity and complexity quantification ally via stability factor η, anti-noise factor ρ and the runtime of each algorithm. FAST (Features from Accelerated Segment Test). This detector uses the intensities of surrounding pixels to detect features. It shows how machine learning can be used to improve even further the speed of the detector. The FAST corner detector is considered an appealing feature detector due to its efficiency and fast performance and less intermediate memory requirements.