| 1. | Feature Set for Indexing in Content Based Image Retrieval of Cervical Cyto Images Download PDF | |
| Authors | Nallaperumal Krishnan, S. Allwin, S.Pradeep Kumar Kenny | |
| Abstract | Content based image retrieval is a technique which uses visual contents to retrieve images tored in large databases. The visual contents normally refer to color, shape, texture and spatial layout. This technique when implied to the medical field is called medical CBIR. It provides doctors with a powerful tool to make accurate diagnosis. This concept tomated the work of a doctor and hence increases accuracy. The doctor can also get a list of similar cases and see what has been administered to such persons in the past.Medical CBIR is now applied for most medical applications as prescribed by the DICOM standard. But there isn’t any standard prescribed for cyto images nor has there been a approach to index and retrieve these kind of images. So we in this paper have tired to index and create a standard for cervical cyto images | |
| Keywords | CBIR, Medical CBIR, Cervical Cytology, Cervical | |
| 2. | AFCNN Framework for Connected Component Detector Download PDF | |
| Authors | S.Senthilkumar | |
| Abstract | This paper demonstrates two new fourth order four stage Root Mean Square (RKARMS(4,4)) and Heronian mean (RKAHeM(4,4)) techniques are proposed for connected component detector by exploiting the latency properties of AFCNNs. It is observed that the simulation results shows that the proposed method has better performance. | |
| Keywords | New RKARMS(4,4) and RKAHeM(4,4) Techniques, Connected Component Detector, Advanced Fuzzy Cellular Neural Network | |