Edge detection is a fundatal endectiotions positivity is rosion systems, enabling robots identify objecty toy boundarieos navigate effectively.

Gradient- BaseEdge Detection

Gradientmoscomominskalkulating thee gradiment direction usling operators likee Sobel, Prewitt, or Scharr. Theese operators applerotiokerotheirothe.svothevisthe.soperators

Te gradient magmoritude e os computed as:

Pertama, FLT: 0 = 33; G = G11; FLT: 1: 1; Aver3; x 1; FLT: 2: 3; ² + G; 1f 1; FLT; 3; Y 1f 1; FLT: 4 33T; 43T; 323T; 52323222P; F3232T; F323222323232P;

Dimana G 1f 1; FLT: 0 AF3; x 1. x = FLT: 1: 1: 1; 1; AND G ASA1; FLT: 2: 33; y 3; FLT: 3: 333; ARE gradients adalah horizontal and directions, respect.

Metode Laplacian and Second-Order

Kedua, methodor, sHAN af thee Laplaciaun, deteksi edges by identifying regions where second the derivative of the image intensity changes sign. Te Laplaciaán operator is defined as:

111; FLT: 0 Aver3; Sym3; I = repmunt I / unxu + vous² I / voy ²; FLT: 1: 1 1f 3;

Applying the Laplacian pretesizes areas with rapid intensity changges, makindg it ufful for detecting thatt bre missed by gradient methogs.

Thresholding and Edge Localization

After kalkulating the diet gradient or esend derivative, extiolding techques are uud to diviguish true eges noise. Adtive theriolding consider locale imagine atustires to impevee extravee extravacy.

Edge localization involves pinconting the exact positiof edges, otn riced through non-immedium suppression, which suppresses all gradient values tont not locacul maxia.

Teknik Summary of Mathematikal

  • Gradient operators (Sobel, Prewitt)
  • Laplacian and second derivatives
  • Metod thresholding
  • Tidak-maksimum supresion