Pengelompokan

Assalamualaikum Wr. Wb dan salam sejahtera bagi semua, sudah lama saya tidak menulis disini dan akhirnya pada kesempatan kali ini saya di berikan kesempatan lagi untuk menulis.

Kali ini saya akan membahas tentang sebuah paper yang bersumber dari http://ieeexplore.ieee.org/document/7353157/?reload=true  khususnya di bagian Abstrak, dimana saya di tugaskan untuk mengelompokan bagian tersebut kedalam 4 kelompok :

1. Latar belakang/ pengantar
2. Tujuan Penelitian
3. Metode yang digunakan 
4. hasil/ kesimpulan

Latar Belakang 

Edge-based active contour models are effective in segmenting images with intensity inhomogeneity but often fail when applied to images containing poorly defined boundaries, such as in medical images.Traditional edge-stop functions (ESFs) utilize only gradient information, which fails to stop contour evolution at such boundaries because of the small gradient magnitudes.

Tujuan Penelitian

  A framework to construct a group of ESFs for edge-based active contour models to segment objects with poorly defined boundaries. 

Metode yang digunakan

In our framework, which incorporates gradient information as well as probability scores from a standard classifier, the ESF can be constructed from any classification algorithm and applied to any edge-based model using a level set method.

Kesimpulan

Experiments on medical images using the distance regularized level set for edge-based active contour models as well as the k-nearest neighbours and the support vector machine confirm the effectiveness of the proposed approach.

Terima Kasih.

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