Traditional thermographic methods, such as pulsed thermography (PT), have two major disadvantages: the quantity of data collected, and they typically are spatially discrete inspections focusing on an area at a time. Previous work by the authors developed an algorithm that was applied to PT data to autonomously detect and quantify lateral corrosion with an absolute error of 3%, thereby reducing the need for a highly trained operator to analyze a large amount of thermal data. Line scanning thermography (LST) uses a dynamic light source to allow for continuous inspection; however, it typically uses a laser to create a line of heat that moves across the sample. In the presented work, to reduce the health and safety concerns related to the use of lasers, a lower-cost and safer method for LST which uses an aluminum elliptical reflector was used and combined with an autonomous defect detection algorithm. The dynamic heat source creates the need for a different approach to post-processing thermal data which now contained both spatial and temporal variation. A regime was developed that creates a quasi-static matrix which allowed the autonomous detection and quantification algorithm to be applied in the same manner as with PT data. Inspection of an acrylic plate with flat bottom hole defects has shown promising results. The method was able to detect defects of 3 mm diameter at a depth of 2 mm using a scanning speed of 6 mm/s and a frame rate of 155 Hz with no noise reduction. Furthermore, initial inspections on a mild steel sample with undercoating corrosion have shown that LST can be used to detect and quantify the extent of corrosion using a frame rate of 200 Hz and a scanning speed of 3.64 mm/s.