INTERNATIONAL JOURNA L OF ENGINEERING SCI ENCES & RESEARCH TECHNOLOGY A Survey Paper On Cashew Kernels Classification Using Color Features & Computer Revelation System .

Cashew is a commercial commodity that plays a major role in earning foreign revenue among export commodities in India. The purpose of this research work is to expl ore image processing techniques and approaches on cashew variety identification based on their kernel s. end users. Our primary objective is to develop a co st Colour features in the RGB (red-green network is trained to classify sample cashew kernel s. An intelligent classification system based on co mputer vision system can be developed for automated grading an will solve the major problems of many of the cashew export industries also, gives justice to the cashe w growing farmers in accurate grading. The classification sys tem is evaluated on cashew k result of our study shows that, the system gives ab out 80% classification rate. Computer vision has be en successfully adopted for the quality analysis of meat and fish, pizza, cheese, and bread. Likewise grain quality an d have been examined by this technique. This paper pr esents the significant elements of a computer visio n system and emphasizes the important aspects of the image processing techn ique coupled with a review of the most recent developments thro ughout the food industry. Abstract Cashew is a commercial commodity that plays a major role in earning foreign revenue among export commodities in India. The purpose of this research work is to expl ore image processing techniques and approaches on cashew variety identification based on their kernel s. Color is an important quality factor for grading, marketi ng, and end users. Our primary objective is to develop a co st -effective intelligent model to identify the cashew kernels. green -blue) color space are extracted and computed. A feed network is trained to classify sample cashew kernel s. An intelligent classification system based on co mputer vision system can be developed for automated grading an d sorting to speed up the classification of cashew kernels. This will solve the major problems of many of the cashew export industries also, gives justice to the cashe w growing farmers in accurate grading. The classification sys tem is evaluated on cashew k ernels of 6 different grades. The result of our study shows that, the system gives ab out 80% classification rate. Computer vision has be en successfully adopted for the quality analysis of meat and fish, pizza, cheese, and bread. Likewise grain quality an d have been examined by this technique. This paper pr esents the significant elements of a computer visio n system and the important aspects of the image processing techn ique coupled with a review of the most recent ughout the food industry. features, cashew kernel, grading, Neural Network. Cashew is a commercial commodity that plays a major role in earning foreign revenue among export commodities in India. The purpose of this research work is to expl ore image processing techniques and approaches on Indian is an important quality factor for grading, marketi ng, and effective intelligent model to identify the cashew kernels. space are extracted and computed. A feed -forward neural network is trained to classify sample cashew kernel s. An intelligent classification system based on co mputer vision d sorting to speed up the classification of cashew kernels. This will solve the major problems of many of the cashew export industries also, gives justice to the cashe w growing ernels of 6 different grades. The result of our study shows that, the system gives ab out 80% classification rate. Computer vision has be en successfully adopted for the quality analysis of meat and fish, pizza, cheese, and bread. Likewise grain quality an d characteristics have been examined by this technique. This paper pr esents the significant elements of a computer visio n system and the important aspects of the image processing techn ique coupled with a review of the most recent