关键词: 视觉词袋特征, 图像分割, 图像分类

Abstract: The regular grid is a popular image detection method in visual bag of words model. This method extracts all image blocks, and obtains complete image information of background blocks and object blocks. In fact, the extracted background block information could confuse classification result. Taking “motorbike” and “cars” images as examples, their background features are similar, and mostly are roads. Some classical classification methods possible divide them into the same category. It can be seen that background information will affect image classification results. So, this paper proposes an image classification method based on extracting bag of words features of object region. Firstly, the background information is removed by image segmentation, and the object area is extracted. Then, bag of words features are extracted for object area. Finally, SVM is used to classify images. The method proposed in this paper is evaluated in PASCAL VOC2006 and PASCAL VOC2010 datasets, and experimental results show that the proposed method has better performance.

Key words: visual bag of words feature, image segmentation, image classification