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Program
Flower Recognition
꽃 2조 아
Past
Present
Future
꽃 사진 추가
LAB를 이용, 꽃잎추출
모양 인식 알고리즘 추가
색상을 기준으로
- 노랑
- 빨강
- 파랑
- 초록 & others
전반적인 순
서
꽃잎추출  특징추출  값 추출 & data화 유사도 비교
CBIR
CBIR
(내용기반 이미지검색)
C o n t e n t B a s e d I m a g e R e t r i e v a l
…(중략)… the problem of searching for digital images in
large databases. Content-based image retrieval is opposed to
traditional concept-based approaches (see Concept based
image indexing).
"Content-based" means that the search analyzes the
contents of the image rather than the metadata such as
keywords, tags, or descriptions associated with the image.
The term "content" in this context might refer to colors,
shapes, textures, or any other information that can be
derived from the image itself. …(중략)…
Colors
Functions
Colors
Textures
Shapes
- HSV histogram
- Auto correlogram
- Color moments
- Gavor wavelet
- Wavelet transform
- ACO
- Descriptor for shapes
Functions about shapes -
ACO
ACO
(개미 군체 알고리즘)
A n t s C o l o n y A l g o r i t h m
- 실제 개미들이 먹이까지 가장 짧은 경로를 찾
는 것을 모방한 알고리즘
- 짧은 길 일수록 개미들의 왕래가 잦아지면서
페로몬의 향기가 짙어짐
- 모든 개미가 모든 Node를 거치면 종료
 크기 차이, 이미지 회전에 강하다는 장점
Functions about shapes -
ACO
Functions about shapes -
ACO
Functions about shapes -
ACO
Functions about shapes -
ACO
Functions about shapes – Descriptor for shapes
수직직선과 수평직선을 그려서 직선의 거리 차가
가장 짧을수록 유사한 이미지
Distance algorithms
- L1
- L2 (Euclidian)
- Minkowski
- Correlation
- Cosine Correlation
- City Block
Distance algorithms
- L1
- L2 (Euclidian)
- Minkowski
- Correlation
- Cosine Correlation
- City Block
계획
- 사진 추가
- algorithms에 대한 이해
- Code정리
- 최종 보고서 작성
Q & A
Thank you

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