2004-05 MODEL PAPER

MCA 3.1.5

COMPUTER VISION AND PATTERN ANALYSIS

Elective III

First Question is Compulsory

Answer any four from the remaining

Answer all parts of any Question at one place.

Time: 3 Hrs.
Max. Marks: 100

1. (a) Define Distance and Connectivity.
(b) Define HIT-or-MISS Transformation.
(c) Define Chain Code. Give it's Application.
(d) Define Euler's Number.
(e) Define C lustering. Briefly Explain it's Importance

2. (a) Define an Edge; Explain Various Edge Enhancement Filters.
(b) Define Image Segmentation. Give a method of image segmentation.

3. (a) Define Skeletanization. Explain it's Application in Pattern Analysis.
(b) Define Thinning & Thickening.

4. (a) Define Region Identification. Give an Algorithm for Region Identification.
(b) Define and Explain Fourier Transforms of Boundaries.

5. (a) Define Convex hull. Give it's Application in Pattern Analysis.
(b) Define and Explain Moments in Detail.

6. (a) Explain Classification Learning.
(b) Explain the Application of Graph Theory in Object Recognition.

7. (a) Define Hierarchical Clustering. Give one Algorithm for above purpose.
(b) Define Partitional Clustering. Give K-Means Algorithm for the above purpose.

8. (a) Give McCulloch - Pitts Model of ANN.
(b) Give McCulloch - Pitts Neuron Model for AND Function.
(c) Briefly Explain Application of Fuzzy Logic in Pattern Analysis.