An effective and improved system is necessary to fulfill the demand in the agriculture industry and the customers to identify the quality of the fruits. Based on the quality of the fruits, the farmers can increase the market prize and also the customers will get a greater satisfaction of consuming quality fruit for better healthy life. A method to identify and classify the quality of fruits using image processing techniques is proposed in this paper. Image Processing steps like image acquisition, pre- processing is carried out both for the testing and training phase. Feature extraction is achieved through Stationary Wavelet Transform (SWT). The GLCM features are used to categorize the fruit disease using Support Vector Machine (SVM) Classifiers. A robust object recognition using edge and texture feature extraction method is presented in this work. The system proposes new approach in object recognition in extension with local binary pattern and ternary pattern called DRLBP and DRLTP. The proposed system will help agriculture industry for not only fruit quality detection but can be used effectively for disease detection also by using the external property of the fruit such as shape, size and color.