arXiv:1205.4831
Gray Level Co-Occurrence Matrices: Generalisation and Some New Features
원문 초록
Gray Level Co-occurrence Matrices (GLCM) are one of the earliest techniques used for image texture analysis. In this paper we defined a new feature called trace extracted from the GLCM and its implications in texture analysis are discussed in the context of Content Based Image Retrieval (CBIR). The theoretical extension of GLCM to n-dimensional gray scale images are also discussed. The results indicate that trace features outperform Haralick features when applied to CBIR.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Semantically-Aware Relevance Measure for Content-Based Medical Image Retrieval Evaluation
Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
Orchestrator-Agent Trust: A Modular Agentic AI Visual Classification System with Trust-Aware Orchestration and RAG-Based Reasoning
Improving Personalized Search with Regularized Low-Rank Parameter Updates
SORCE: Small Object Retrieval in Complex Environments
토론
이 논문과 연결된 포럼 글이 아직 없습니다.