1. Automatic dog’s excrement detection system
自動狗屎偵測系統
Automatic dog’s excrement detection system
指導教授：方瓊瑤
專題學生：謝欣紘

2. Outline Introduction System Flowchart
Dog’s Excrement Candidate Extraction
K-means Clustering
Experimental Results
Conclusions and Future Work

3. Introdution Motivation The processes of the system
Maintain enviromental cleanliness
Avoid stepping in dog feces
The processes of the system
Dog’s excrement detection
Noise removement
Connected components
Automatically selects the k-means results
Showing warnings

4. System Flowchart 狗屎定位 連續影像輸入 影像特徵擷取 否 特徵是否成功擷取? 是 雜訊去除 區塊連結 狗屎特徵擷取
狗屎驗證
影像特徵擷取

5. Dog’s Excrement Candidate Extraction
Color space selection
RGB color space
HSV color space

6. Candidate Extraction

7. Varience Calculation n：為pixel總數 xi：為每一pixel在x座標的值 yi：為每一pixel在y座標的值

8. Noise Removement

9. Connected Component

10. K-means Clustering K-means clustering
partition n observations into k clusters
each observation belongs to the cluster with the nearest mean
a set of observations (x1, x2, …, xn)
μi is the mean of points in Si
S = {S1, S2, …, Sk}

11. cluster centers locations
Ask User how many
clusters they’d like.
(e.g. k=5).
Random select k
cluster centers locations
Each datapoint finds out which Center it’s closest to. (Thus each Center “owns” a set of datapoints)
Each cluster fine the centroid of the points it owns.
According to the new center, we can re-classify the entire training set. For each data in the training set, find the new nearest cluster center and classify data as a member of new cluster.
…and jumps to there
…repeat step 3 to 5 until terminated
Presented by Kuei-Hsien

12. K-means Results
K = 2
K = 3
K = 4
K = 5

13. Experimental Results
Dog’s excrement

14. Experimental Results(cont.)
Dog’s excrement

15. Experimental Results(cont.)
Road

16. Warning Lights
警示燈

17. Accuracy rate Dog’s excrement38張、Road 7張 35/38 92.1% 2/50 4% 3/38 2.9%
35/ %
2/50 4%
3/ %
48/ %

18. Failed example

19. Conclusions and Future Work
Distinguish between dog’s excrement and road
Feature Extraction
K-means Clustering
Future work
Distinguish between dog’s excrement and other things
Improve execution time