Texture slide

Here’s a simpler version:


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### **1. What Are Texture Features?**

- **What it is:** Texture features are patterns or designs in images.

- **Why it matters:** They help in tasks like recognizing objects, improving image quality, and teaching machines to understand images.


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### **2. Grouping Textures**

- **Benefits:** Grouping textures makes it easier to analyze and use in art, design, and factories.

- **Problems:** Grouping can oversimplify and make unique textures less noticeable or limit creativity.


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### **3. Ways to Study Textures**

- **Statistical Methods:** Use numbers to study patterns in images (like GLCM).

- **Structural Methods:** Focus on how parts of textures are arranged.

- **Spectral Methods:** Study textures using tools like Fourier transforms.

- **Mixed Methods:** Combine all these for better results.


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### **4. What Is GLCM?**

- **What it does:** GLCM looks at how often certain patterns show up in images.

- **Where it’s used:** In medical scans, remote sensing, and texture studies.


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### **5. Structural Textures**

- **Basic Parts:** Things like edges, corners, and shapes that build textures.

- **Patterns:** Designs like stripes, grids, or waves.

- **Uses:** Checking materials for problems and improving designs.


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### **6. Spectral Texture Analysis**

- **What it is:** A way to study detailed patterns in images using special tools.

- **Why it’s useful:** It helps to separate and classify textures better.


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### **7. Textures and AI**

- **Why it matters:** AI uses textures to identify objects and understand images more clearly.


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### **8. Example: Medical Imaging**

- **Starting out:** Textures help find problems like tumors in scans.

- **Progress:** New tools make it faster and more accurate, helping doctors catch issues early.


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### **9. Challenges with Textures**

- **Problems:** Noisy images, similar-looking textures, and confusion in analysis.

- **Fixes:** Use better tools, machine learning, and standard rules.


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### **10. The Future of Textures**

- **What’s next:** AI will get better at understanding textures for robots, AR, and more.

- **Being fair:** Ensuring texture data in AI is used responsibly and without bias.


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Let me know if this is clearer!

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