The goal of this research is to recognize an object and its orientation by using stereo camera. The principle of object orientation recognition in this paper was based on the Scale Invariant Feature Transform (SIFT) and Support Vector Machine (SVM). SIFT was success on object recognition but it had a problem on recognizing the object orientation. Object recognition is important for industrial application, for example: many industries using industrial robot hand to grab some products. Not only object recognition will be needed in this process but also object orientation recognition. Object orientation is important for industrial robot hand to grab the object. In this paper we used SVM to recognize object orientation. SVM has been known as a promising method for classification accuracy and its generalization ability. In our experiments, we used stereo camera system because it was better than only by using one camera. Stereo camera system provided more information compare to single camera. I also implemented object orientation recognition for industrial robot hand. In the real application, our proposed method was used to recognize an object orientation. The gained information then became the input for the industrial robot hand which made it able to rotate the first object and put it above the second object with the same orientation.

The goal of this research is to recognize an object and its orientation by using stereo camera. The principle of object orientation recognition in this paper was based on the Scale Invariant Feature Transform (SIFT) and Support Vector Machine (SVM). SIFT was success on object recognition but it had a problem on recognizing the object orientation. Object recognition is important for industrial application, for example: many industries using industrial robot hand to grab some products. Not only object recognition will be needed in this process but also object orientation recognition. Object orientation is important for industrial robot hand to grab the object. In this paper we used SVM to recognize object orientation. SVM has been known as a promising method for classification accuracy and its generalization ability. In our experiments, we used stereo camera system because it was better than only by using one camera. Stereo camera system provided more information compare to single camera. I also implemented object orientation recognition for industrial robot hand. In the real application, our proposed method was used to recognize an object orientation. The gained information then became the input for the industrial robot hand which made it able to rotate the first object and put it above the second object with the same orientation.

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