Combining Morphological Feature Extraction and Geometric Hashing for Three-Dimensional Object Recognition Using Range Images

This paper presents a new approach for model-based object recognition with range images by combining morphological feature extraction and geometric hashing. In low-level processing, range images are segmented into 3D-connected surface patches. In middle-level processing, each connected component is processed by using morphological operations to extract the skeletons of high-variation regions. These skeleton points can be viewed as invariant salient feature primitives. In high-level processing, geometric hashing is used to recognize objects. We also use a basis-similarity constraint to reduce the number of spurious hypotheses. Experimental results have shown that the proposed method is effective and has great potential for model-based object recognition using range images.

並列關鍵字

computer vision ； object recognition ； range image processing ； feature extraction ； geometric hashing

被引用紀錄

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黃彥誠（2008）。一個對於高光譜影像的模擬退火特徵齊一化波段選取方式〔碩士論文，國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2403200815240400

國際替代計量

Combining Morphological Feature Extraction and Geometric Hashing for Three-Dimensional Object Recognition Using Range Images

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