Academic Work - Computer Vision

Confidence doesn’t always arrive with a bold entrance. Sometimes, it builds quietly, step by step, as we show up for ourselves day after day. It grows when we choose to try, even when we’re unsure of the outcome. Every time you take action despite self-doubt, you reinforce the belief that you’re capable. Confidence isn’t about having all the answers — it’s about trusting that you can figure it out along the way.

The key to making things happen isn’t waiting for the perfect moment; it’s starting with what you have, where you are. Big goals can feel overwhelming when viewed all at once, but momentum builds through small, consistent action. Whether you’re working toward a personal milestone or a professional dream, progress comes from showing up — not perfectly, but persistently. Action creates clarity, and over time, those steps forward add up to something real.

You don’t need to be fearless to reach your goals, you just need to be willing. Willing to try, willing to learn, and willing to believe that you’re capable of more than you know. The road may not always be smooth, but growth rarely is. What matters most is that you keep going, keep learning, and keep believing in the version of yourself you’re becoming.

• Digital Image Processing and Image Preprocessing

  The two documents below demonstrate how an image can be digitally processed and preprocessed through the use of image modifying techniques and the image processing library OpenCV. The work performed in the first document features the altering of the Lena image, performing actions such as resizing, cropping, color manipulation, and binarization. The second document focuses on an image of a human blood vessel and making the image clearer through image augmentations, histogram stretching, CLAHE, RGB normalization, and brightness and contrast enhancement.

• Morphological Image Processing

  This document demonstrates image processing through using the geometry within the images. Through boundary extraction, closing, region filling, and connected components, morphological processing can help create an image that is easier to understand.

• Object Detection

  This document demonstrates Haar cascade classifying using blood vessel analysis and license plate reading. The blood vessels are dilated, closed, and have connected components identified. The license plate reading process uses erosion, edge detection, contour detection, and masking to determine the license plate number.

• YOLO

  This document demonstrates the use of YOLO (You Only Look Once) where filter boxes are used to identify specific objects in an image and a video.