Half of all men and one-third of all women in the US develop cancer during their lifetimes. Today, millions of people are living with cancer or have had cancer. The risk of developing many types of cancer can be reduced by changes in a person’s lifestyle, for example, by staying away from tobacco, limiting time in the sun, being physically active and healthy eating. Our aim is to find the types of skin cancer by various techniques of image processing. This paper presents a new approach for skin cancer detection and analysis from given photograph of patient’s cancer affected area, which can be used to automate the diagnosis of skin cancer. The proposed scheme uses two methods for classification of skin cancer- ABCD rule with good diagnostic accuracy worldwide is used in diagnostic system as a base and finally the feature extraction is done using principal component analysis. These methods are compared for their effectiveness.