LITERATURE REVIEW OF IMAGE SEGMENTATION TECHNIQUES:
Diabetic foot ulcer on a patient is been identified by several process of implementation. Before segmentation, identification is carried over for identifying the damaged tissue and the location of the nerve damage by SVM based identification and foot anthropometry by using hyper spectral imaging process . Segmentation on foot ulcer is been carried by several process which is used to determine the area of the wound by color feature analysis which is been caused by low nutrients, pressure on the foot and low nutrients on the affected tissue.
a) Modified Chain Vase Algorithm:
On 2017, Modified Chan vase algorithm  method named global Region Based chain Vase Algorithm is been implemented to detect foot ulcer by body temperature and analyzed by IR thermal image processing and several iteration process is carried out and ROI is measured. The edges of foot images is taken by the infrared camera where the segmentation boundary implicit with the level set function so the initial curve is placed on the image. The modified chain vase is based on morphological processing where the temperature is measured on the risky area on the foot. In this the input image is been processed by different types of masks and initiate Chain-Vase vector to start the iteration. The iteration is carried over until the desired results are obtained. After the iteration process in the global region based segmentation the pale pale is left in the foot, where remaining foot may be damaged that part is eliminated to save the entire foot.
b) Accelerated Mean Shift Algorithm:
On 2016Accelerated mean shift algorithm is used to accelerate the wound area and by using color coding feature the boundary area is detected, further MATLAB application is used to process the captured image where color based segmentation is used to detect skin color, wound boundary . The mean-shift filtering algorithm is been suitable for parallel implementation, where it belongs to the density estimation process based non parametric clustering process, in which the feature space can be considered as the empirical probability density function of the parameter. In general, the mean-shift algorithm models the feature vectors associated with each pixel (e.g., color and position in the image grid) as samples from an unknown probability density function f(x) and then finds clusters in n number of distribution . Another method is based on automatic assessment of diabetic foot ulcer based on wound area determination, color
segmentation is processed by wound image assessment algorithm where image capture box is used to capture the image by warm light LED light which is compact, inexpensive or by using MATLAB application and the color segmentation is carried by accelerated mean shift algorithm