A study on automated algorithm for image detection and measurement

Image segmentation is a process of partitioning an image into many regions based on application. Object detection is the process of detecting the locations and sizes of all objects in an image. Detection and measurement from the macula can be determined by comparing the original image with background image. Disease severity can be concluded by the measurement of the sizes of the fluid deposits and comparing them to the retina normal size. Many algorithms have been indentified for automatic detection, segmentation, and measurement on 2D retinal images. Measurements are calculated based on mathematical functions and numerical methods using polyarea function. The first step in image processing for measurement detection is preprocessing and segmentation. Preprocessing operations includes image filtration, correction of non-uniform illumination, and colour contrast enhancement. This automated algorithm help's ophthalmologists to monitor the progression of diabetic retinopathy more accurately. In manual analysis a huge amount of time and effort is required. To overcome this automated detection method is used, which reduce clinician's burden per patient and time.