Display image on canvas

Full 8-round encryption. - Creates ONE SkewTentMap(x0, mu) instance if tent_map is None. - Saves map state BEFORE each round for use

Load TTEH key from file with all decryption data. Args: filepath: Path to key file Returns: Dictionary containi

Compute correlation for given pixel pairs.

Create an image display panel

Generate TTEH encryption key with random parameters if not provided. Args: x0: Initial condition for Skew Tent Map (random if No

Apply forward MPHT row-by-row to every adjacent pixel pair. Paper equations 11-12 (fingerprint) and 13-14 (substitution): alpha = (a +

Full security analysis for one image. 1. Encrypt orig → (cipher, round_states, substitution_data) 2. Create modified image: flip pixel at

Full 8-round decryption — paper Section III-B. Reverses rounds in order: round 8 first, round 1 last. For each round (in reverse):

Generate `length` keystream values. Args: length: Number of keystream values to generate Return

Advance map by one step, return x_{n+1} as float in (0,1). Implements paper equation 16: x_{n+1} = mu * x_n

Save TTEH key to file with all decryption data. Args: key: Key dictionary from generate_key() filepath: Path to save key

Process all .bmp and .png images in image_dir. Print progress: "Processing image N/total: filename" Return DataFrame with one row per ima

Paper equation 26: r = cov(o,c) / sqrt(G(o) * G(c)) Where: cov(o,c) = (1/N) * Σ (oᵢ - mean(o)) * (cᵢ - mean(c)) G(o) = (1/N)

Paper equation 25: H(s) = Σ p(s) * log2(1/p(s)) Compute over all 256 gray levels of the encrypted image. Skip gray levels with zero count

Paper equation 24: NPCR = [Σ D(i,j) / (X*Y)] * 100 D(i,j) = 1 if cipher1(i,j) != cipher2(i,j), else D(i,j) = 0 cipher1 = encryption of or

Paper equation 23: UACI = (1/(X*Y)) * Σ [|C1(i,j) - C2(i,j)| / 255] * 100 Same cipher1 and cipher2 as NPCR. Return percentage float.

Create matplotlib charts

Tab 1: Encrypt / Decrypt

Create Figure 6: Entropy bar chart - Bar chart, 80 images - Horizontal ideal line at 8.0

Create Figure 7: NPCR bar chart - Bar chart, 80 images - Horizontal ideal line at 99.6093

Create Figure 8: UACI bar chart - Bar chart, 80 images - Horizontal ideal line at 33.4635

Create Figure 9: Correlation horizontal bar chart - Horizontal bar chart matching paper Fig 9 style - Show mean correlation for three dir

One encryption round — paper Section III-A, Steps 1-4, Figure 4. Step 1: Apply mpht_forward to img → f_trans (eq. 11-12) Step 2: Ap

Generate synthetic fingerprint dataset if data/samples/ is empty. Args: num_images: Number of synthetic images to generate

Generate a realistic synthetic fingerprint image. Used when FVC2004 dataset is unavailable. Algorithm: 1. Create ridge pattern

Return current map value (for saving state before round). Returns: Current state x_n

Main analysis script

Apply inverse MPHT row-by-row to every adjacent pixel pair. Paper equations 21-22: b = (beta - alpha) mod 2^n a = (2*alpha - beta

Print final summary table matching paper results.

Restore map to a previous state (for decryption replay). Args: x: State value to restore, must satisfy 0 < x < 1

Update matplotlib charts

Update metrics labels with color coding

Initialize Skew Tent Map with parameters. Args: x0: initial condition, must satisfy 0 < x0 < 1 mu: m

Decrypt the encrypted image

Decrypt image using key from file. Args: cipher: Encrypted image keyfile: Path to key file round_states: Optio

Encrypt the loaded image and save both encrypted image and key

Encrypt image using key from file. Args: img: Original fingerprint image keyfile: Path to key file Returns:

Export encrypted image to file

Generate and display random key, update GUI fields

Load an encrypted image and its key file

Load an image file

Load key from file with decryption data

Save current key to file