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// 距离变换（纯 MoonBit）
///|
/// 距离变换。对二值图（非零为前景）计算每个前景像素到最近背景像素的距离。
/// 适用于灰度图（channels=1）或 RGB/RGBA 图（channels=3/4，取首通道）。
/// distance_type 为距离度量：1=城市距离(L1), 2=欧氏距离(L2近似), 3=棋盘距离(Linf)。
/// 返回 Float 数组，背景像素距离为 0。
pub fn distance_transform(
img : @types.Image,
distance_type? : Int = 2,
) -> Array[Float] raise @types.LoadError {
if distance_type != 1 && distance_type != 2 && distance_type != 3 {
raise @types.LoadError::DecodeFailed(
"distance_type 必须为 1(L1), 2(L2), 3(Linf)",
)
}
if img.channels != 1 && img.channels != 3 && img.channels != 4 {
raise @types.LoadError::DecodeFailed(
"distance_transform 仅支持 channels=1/3/4",
)
}
let w = img.width
let h = img.height
let n = w * h
if n == 0 {
return []
}
// 转为二值（非零为前景）
let binary : Array[Bool] = Array::make(n, false)
let ch = img.channels
for i in 0..<n {
binary[i] = img.data[i * ch].to_int() > 0
}
// 两遍扫描算法
let dist : Array[Float] = Array::make(n, 10000000000.0F)
// 初始化：背景为 0，前景为无穷大
for i in 0..<n {
if !binary[i] {
dist[i] = 0.0F
}
}
// 距离掩码
let (mask1, mask2) = match distance_type {
1 => ([(0, -1, 1.0F), (-1, 0, 1.0F)], [(0, 1, 1.0F), (1, 0, 1.0F)])
3 => ([(0, -1, 1.0F), (-1, 0, 1.0F)], [(0, 1, 1.0F), (1, 0, 1.0F)])
_ =>
(
[(0, -1, 1.0F), (-1, 0, 1.0F), (-1, -1, 1.414F), (-1, 1, 1.414F)],
[(0, 1, 1.0F), (1, 0, 1.0F), (1, 1, 1.414F), (1, -1, 1.414F)],
)
}
// 前向扫描（左上到右下）
// 内部区域：x >= 1 && y >= 1 && y < h - 1
for y in 1..<(h - 1) {
for x in 1..<w {
let idx = y * w + x
if !binary[idx] {
continue
}
for m in mask1 {
let (dx, dy, d) = m
let nd = dist[(y + dy) * w + (x + dx)] + d
if nd < dist[idx] {
dist[idx] = nd
}
}
}
}
// 边界行
for y in 0..<h {
if y >= 1 && y < h - 1 {
continue
}
for x in 0..<w {
let idx = y * w + x
if !binary[idx] {
continue
}
for m in mask1 {
let (dx, dy, d) = m
let nx = x + dx
let ny = y + dy
if nx >= 0 && nx < w && ny >= 0 && ny < h {
let nd = dist[ny * w + nx] + d
if nd < dist[idx] {
dist[idx] = nd
}
}
}
}
}
// 内部行的边界列
for y in 1..<(h - 1) {
let idx = y * w
if binary[idx] {
for m in mask1 {
let (dx, dy, d) = m
let nx = dx
let ny = y + dy
if nx >= 0 && ny >= 0 && ny < h {
let nd = dist[ny * w + nx] + d
if nd < dist[idx] {
dist[idx] = nd
}
}
}
}
}
// 反向扫描（右下到左上）
// 内部区域：x < w - 1 && y >= 1 && y < h - 1
for y in 1..<(h - 1) {
for x in 0..<(w - 1) {
let idx = y * w + x
if !binary[idx] {
continue
}
for m in mask2 {
let (dx, dy, d) = m
let nd = dist[(y + dy) * w + (x + dx)] + d
if nd < dist[idx] {
dist[idx] = nd
}
}
}
}
// 边界行
for yy in 0..<h {
if yy >= 1 && yy < h - 1 {
continue
}
let y = yy
for xx in 0..<w {
let x = w - 1 - xx
let idx = y * w + x
if !binary[idx] {
continue
}
for m in mask2 {
let (dx, dy, d) = m
let nx = x + dx
let ny = y + dy
if nx >= 0 && nx < w && ny >= 0 && ny < h {
let nd = dist[ny * w + nx] + d
if nd < dist[idx] {
dist[idx] = nd
}
}
}
}
}
// 内部行的边界列
for y in 1..<(h - 1) {
let x = w - 1
let idx = y * w + x
if binary[idx] {
for m in mask2 {
let (dx, dy, d) = m
let nx = x + dx
let ny = y + dy
if nx >= 0 && nx < w && ny >= 0 && ny < h {
let nd = dist[ny * w + nx] + d
if nd < dist[idx] {
dist[idx] = nd
}
}
}
}
}
dist
}
///|
/// 距离变换可视化。将距离变换结果归一化到 [0, 255] 并返回灰度图。
pub fn visualize_distance_transform(
dist : Array[Float],
w : Int,
h : Int,
) -> @types.Image {
let n = w * h
let out : Array[Byte] = Array::make(n, b'\x00')
if n == 0 {
return @types.Image::{
width: 0,
height: 0,
channels: 1,
data: Bytes::from_array([]),
}
}
let mut max_dist = 0.0F
for i in 0..<n {
if dist[i] > max_dist {
max_dist = dist[i]
}
}
if max_dist > 0.0F {
for i in 0..<n {
let val = (dist[i] / max_dist * 255.0F).to_int()
out[i] = val.clamp(min=0, max=255).to_byte()
}
}
@types.Image::{
width: w,
height: h,
channels: 1,
data: Bytes::from_array(out),
}
}
///|
/// 骨架化（基于距离变换）。
/// 提取二值图的骨架（中轴线）。
/// 适用于灰度图（channels=1）或 RGB/RGBA 图（channels=3/4，取首通道）。
pub fn skeletonize(img : @types.Image) -> @types.Image raise @types.LoadError {
if img.channels != 1 && img.channels != 3 && img.channels != 4 {
raise @types.LoadError::DecodeFailed("skeletonize 仅支持 channels=1/3/4")
}
let w = img.width
let h = img.height
let n = w * h
if n == 0 {
return img
}
// 计算距离变换
let dist = distance_transform(img, distance_type=2)
// 骨架点：局部最大值
let ch = img.channels
let out : Array[Byte] = Array::make(n * ch, b'\x00')
for y in 1..<(h - 1) {
for x in 1..<(w - 1) {
let idx = y * w + x
if dist[idx] == 0.0F {
continue
}
let mut is_max = true
for dy in -1..<=1 {
for dx in -1..<=1 {
if dx == 0 && dy == 0 {
continue
}
if dist[(y + dy) * w + (x + dx)] > dist[idx] {
is_max = false
break
}
}
if !is_max {
break
}
}
if is_max {
for c in 0..<ch {
if ch == 1 {
out[idx] = b'\xFF'
} else if c < 3 {
out[idx * ch + c] = b'\xFF'
}
}
if ch == 4 {
out[idx * ch + 3] = img.data[idx * ch + 3]
}
}
}
}
@types.Image::{
width: w,
height: h,
channels: ch,
data: Bytes::from_array(out),
}
}